AI Prediction & Forecasting Toolbox - With Just a Case number

Predict the course and outcome of litigation with proprietary legal intelligence

Go beyond legal analytics, case research, and human intuition

Forecast confidently with 85% model accuracy.

Predict the course and outcome of litigation with proprietary legal intelligence

Go beyond legal analytics, case research, and human intuition

Forecast confidently with 85% model accuracy.

A data-reinforced advantage for leading legal professionals

Validated against millions of cases and billions of data points

” Thrilled to announce that all our attorneys at Quinn Emanuel now have access to Pre/Dicta AI’s powerful tool suite. This AI-driven technology uncovers hidden patterns in judicial decisions, helping us deliver exceptional results for our clients. “

Predictive Case Intelligence

Pre/Dicta provides unmatched intelligence for attorneys and litigants throughout the litigation lifecycle, delivering critical insights into case outcomes, parties, judges, and venues.

Comparative Predictions

Corporate Litigation Intelligence

Pricing and Value

Strategic Insights

Alternative Fee Optimization

Offer more creative success-based fee structures that accurately reflect litigation risk.

Example: Silverstone & Hunt is negotiating engagement terms for a breach of fiduciary duty dispute. Pre/Dicta’s analysis indicates a low likelihood of a summary judgment grant alongside an accelerated adjudication timeline. Using this data, Silverstone & Hunt conducts a comparative pricing analysis and risk assessment, ultimately proposing a contingent-fee structure instead of an hourly billing model. This approach maximizes potential revenue from the case while aligning with the client's expectations and the case dynamics.

Panel Counsel Selection

Utilize forecasts comparing law firms’ projected success rates throughout the litigation lifecycle to select the firm most likely to achieve the desired outcome.

Example: ApexTek Industries faces a class action suit involving antitrust allegations. To make an informed decision on legal representation, ApexTek reviews predictive analytics that forecast each law firm’s success rates across the litigation lifecycle. The analysis also includes insights into each firm’s efficiency during discovery and motion practice, helping ApexTek weigh the potential costs and benefits of various firms. Using these forecasts, ApexTek selects a firm with the highest likelihood of delivering a resolution aligned with its business objectives.

Adverse Party Selection and Analysis

Assess whether including or excluding ancillary adverse parties can enhance the likelihood of favorable outcomes, especially in complex cases involving multiple defendants.

Example: VentraBio, a pharmaceutical company, is preparing to file sweeping antitrust allegations against pharmaceutical wholesalers. Their legal team is strategizing whether to include ancillary parties, such as distributors and smaller pharmacies, who may have played a tangential role in alleged price-fixing schemes. Pre/Dicta’s forecasts indicate that including these parties could extend the motion to dismiss timeline by over 100 days. Armed with this data, VentraBio’s legal team conducts a risk-benefit analysis to determine whether the potential benefits of naming ancillary parties outweigh the associated delays.

Venue Selection Analysis

Leverage comparative forecasts to assess optimal venue selection.

Example: GreenSky Innovations, a renewable energy firm, plans to assert its patents against a competitor. Although GreenSky is based in the Western District of Texas (WDTX) and the competitor is headquartered in the Northern District of California (NDCA), Pre/Dicta’s analysis reveals a higher likelihood of surviving a motion to dismiss in the NDCA. Based on this insight, GreenSky files in the NDCA, successfully overcomes the motion to dismiss, and ultimately achieves a favorable settlement.

Downstream Impact Assessment

Before pursuing motions for transfer, reassignment, or disqualification, evaluate their potential impact on each stage of litigation to determine if they will provide a meaningful advantage to the case.

Example: EvoBuild Manufacturing seeks a change of venue to its domicile location. However, Pre/Dicta’s data reveals that the new venue significantly lowers the likelihood of success at the motion to dismiss and summary judgment stages. Based on this insight, EvoBuild’s legal team advises against the transfer and reallocates the budget to strengthen the briefing of the motion to dismiss, adopting a more aggressive strategy in the current venue.

Departmental Resource Allocation

Forecast the resource needs for each matter across the litigation department, assigning partners, associates, and support staff with precision to ensure optimal workload distribution and efficiency.

Example: Johnson & Smith is an insurance defense firm managing a portfolio of 500 active litigations. Pre/Dicta’s insights into motion outcomes and associated timelines allow the firm to assign internal resources in a manner that precisely aligns with the requirements for each case, freeing up significant bandwidth for the firm to take on new cases.

Case Resolution Optimization

Determine the optimal approach to case resolution, either by successful motion practice or settlement.

Example: UnionWorks Logistics is engaged in a contract dispute with a predicted 29% success rate for summary judgment. According to Pre/Dicta’s analysis, the low likelihood of success and the high costs associated with pursuing summary judgment and going to trial lead UnionWorks to conclude that settling during discovery is the most prudent course of action. This strategy minimizes financial risk and avoids the uncertainties of trial, allowing UnionWorks to resolve the dispute at a significantly lower cost compared to potential trial liabilities, aligning with the best interests of their stakeholders.

Executive-Level Guidance

Provide executives and board members with high-level predictive insights about litigation’s potential effects on business performance, shareholder value, and operational continuity.

Example: AlturaMed, a biotech company, is facing a class action FLSA (Fair Labor Standards Act) case concerning overtime pay practices. Pre/Dicta’s data reveals a high likelihood that AlturaMed’s motion to dismiss will be granted, while the probability of prevailing at summary judgment is significantly lower (31%). With this insight, AlturaMed’s board can reasonably expect to avoid prolonged litigation at the early stages, reducing immediate financial and reputational risks. However, given the lower probability of success at summary judgment, the board can prepare for potential settlement discussions or trial proceedings as part of a broader risk management strategy. Pre/Dicta’s timeline prediction also allows the executive team to properly prepare operationally for both possible outcomes, proactively adjusting market forecastings and preparing investors for the range of potential impacts.

Risk & Impact Advisory

Help clients translate litigation risk into business terms, allowing assessment and management of regulatory, operational, and reputational exposure.

Example: NextWave Energy is served with an allegation of corporate malfeasance resulting in environmental contamination. With a 68% likelihood of class certification, Pre/Dicta enables NextWave’s legal team to assess the elevated exposure, advising executives on the potential impact of class-action status on their reputation, operations, and regulatory compliance costs. These insights allow the company to proactively mitigate risks, prepare regulatory responses, manage operational adjustments across departments, and discreetly resolve the allegations against the company.

Outcome Forecasting

Anticipate litigation outcomes and prepare clients for various scenarios, supporting continuity and minimizing business risk.

Example: TransGlobal Logistics is involved in a breach of contract case with an 84% likelihood of successfully transferring venues. Pre/Dicta’s data predicts that in the new venue, dismissal motions are typically resolved within 427 days if granted. If the motion is denied, the court is expected to take about 206 days to rule on the dismissal motion, after which discovery is likely to last approximately 729 days. This forecast enables TransGlobal to anticipate the timeline of litigation phases, allocate resources effectively, and adjust budgets accordingly, ensuring that operational and financial planning is aligned with potential outcomes.

Adverse Outcome Preparation

Develop flexible plans to manage potential litigation outcomes, ensuring business continuity.

Example: PeakTech, a tech company facing allegations of IP theft, consults Pre/Dicta’s data, which shows a high likelihood that the plaintiff will prevail in their motions to compel disclosure of sensitive corporate documentation. With an understanding of the court’s proclivity to grant the plaintiff’s motion, PeakTech’s legal department requests that litigation counsel preemptively prepare a motion for a protective order, safeguarding sensitive information pertaining to new product releases from prying public eyes.

Adaptive Scenario Simulation

Simulate various litigation scenarios, offering clients with a spectrum of strategic choices accompanied by the range of potential outcomes.

Example: BrightLuxe, a cosmetics company defending a consumer fraud claim, sees that class certification is likely (68%). Pre/Dicta runs simulations for various scenarios, including the likelihood of success in motions to compel (72%) and summary judgment (40%). Using these insights, BrightLuxe’s in-house legal team directs their litigation counsel to pursue fact discovery aggressively with the goal of amplifying settlement leverage. They budget accordingly and present their approach to their corporate stakeholders with data-backed justification and explanation.

Litigation Roadmap & Milestone Planning

Map out key litigation stages, empowering clients to make informed decisions at critical points.

Example: VectorGen, a company defending against an employee misclassification lawsuit, uses Pre/Dicta’s roadmap, which projects a 312-day timeline to discovery and 577 days for summary judgment. With this insight, VectorGen aligns its resources and prepares HR and finance for potential operational adjustments, while keeping executives informed of critical litigation milestones.

Litigation Decision Support

Offer guidance on pursuing settlements or proceeding with litigation, tailored to client business priorities.

Example: UnionWorks Logistics faces a contract dispute with only a 29% predicted success rate for summary judgment. Based on Pre/Dicta’s analysis, UnionWorks decides to focus resources on trial preparation rather than summary judgment, budgeting for a potential trial while also engaging in proactive settlement discussions to minimize exposure.

Cross-Functional Impact Advisory

Advise on the impact of legal proceedings on departments like finance, HR, and operations within a client’s organization.

Example: GreenScale Construction is under litigation for environmental compliance issues. Pre/Dicta’s prediction of an 84% likelihood of successful venue transfer and an extended timeline for pre-discovery motions allows GreenScale to plan resource adjustments in finance, HR, and operations, ensuring that departments are prepared for potential impacts and can proactively manage internal communications.

Motion Strategy

Refine dispositive motion practice, tailoring strategy according to the likelihood of a favorable outcome

Example: ClearWave Solutions, a fintech firm, is preparing to petition the Court to dismiss a securities fraud case. Pre/Dicta’s analysis indicates a low likelihood of success for the motion to dismiss. Using this data, ClearWave adopts a strategic approach by narrowly focusing on a few key deficiencies in the pleading. This tactic allows the firm to preserve stronger arguments for later stages of the litigation, ensuring a more effective defense as the case progresses.

Defendant and Venue Strategy

Provide insights for including or excluding defendants strategically, allowing for advantageous venue selection and maximizing chances for dismissal before discovery.

Example: EvoBuild Manufacturing seeks a venue transfer to a jurisdiction with lower plaintiff success rates. With Pre/Dicta’s data showing an 84% likelihood of successful venue transfer, EvoBuild’s legal team adjusts its defense strategy to maximize favorable outcomes in the new district, where motions to dismiss are more frequently granted.

Judge Reassignment Analysis

Assess how a new judge assignment impacts case outcomes and adjusts strategy accordingly.

Example: FusionTech sees its antitrust case reassigned to Judge Jacob Small, who has a 67% rate of granting summary judgment. Pre/Dicta’s insights on the judge’s tendencies allow FusionTech’s legal team to emphasize arguments that align with Judge Ho’s historical preferences, increasing chances of a favorable ruling.

Negotiation Strategy

Leverage AI-based insights to strategically time negotiations, aligning them with procedural pressure.

Example: ZenCorp, in antitrust litigation, relies on Pre/Dicta’s AI-driven predictions to determine that the optimal inflection point for settlement is just after class certification, which is forecast to be denied. By strategically timing their settlement offer based on these insights, ZenCorp optimizes their leverage to resolve the suit when the plaintiff’s settlement floor is likely to be lowest.

Budget Precision

Craft precise and highly-accurate litigation budgets.

Example: MetroHub Retail’s litigation counsel, representing the company in a labor dispute, benefits from Pre/Dicta’s timeline predictions, which help them estimate billable hour requirements across each procedural stage – from pre-discovery (427 days) to trial (197 days). This precision minimizes budget overages and keeps financial planning aligned with litigation stages.

Client Engagement Strategy

Maintain clear, informed communication with clients to ensure alignment and engagement throughout litigation.

PinnacleTech, a telecom giant, is informed by their litigation counsel of the 62% success rate for motions to compel discovery. Sharing these insights increases operational value provided by litigation counsel, allowing in-house counsel to work with the executive team to plan for potential disclosure risks and impacts.

Litigation Timelines

Predict the duration of litigation phases, helping clients plan budgets and allocate resources efficiently.

Example: EchoBank is involved in a class action with a low likelihood of dismissal via the motion to dismiss. Pre/Dicta’s timeline predictions for various stages (e.g. 612 days for discovery) enable EchoBank’s legal team to prepare detailed resource and budget allocations, ensuring smooth operational planning.

Settlement & Negotiation Strategy

Pinpoint optimal negotiation moments by predicting when parties’ leverage or procedural advantages peak.

Example: EchoBank faces a high-stakes class action and knows there’s a 81% chance of class certification. Pre/Dicta helps them identify the peak moment for leverage, allowing the legal team to strategically time a settlement offer to maximize favorable terms before incurring significant discovery costs.

Dismissal Strategy

Understand whether to reveal or conceal the strongest arguments of your case at early stages of litigation.

Example: OmniLab Pharmaceuticals, defending a product liability suit, is advised by Pre/Dicta’s data to withhold its most compelling arguments initially. With a low predicted 29% success rate for early dismissal, OmniLab’s legal team opts to save key evidence for trial, preserving their strongest defenses until later stages.

Risk-Based Fixed Fee with Contingency Bonus

Establish a fixed fee for pre-discovery motions, with a performance-based bonus if an early dismissal is achieved.

Example: OppenMeds Pharmaceuticals, facing multi-district product liability litigation, uses Pre/Dicta’s data to learn there’s a 57% likelihood of dismissal in pre-discovery motions. The firm offers a fixed fee for the pre-discovery phase, with a contingency bonus payable if the dismissal is granted. This structure aligns with predicted timelines and incentivizes early resolution.

Phased Success Fee Based on Litigation Milestones

Implement a phased success fee tied to achieving specific litigation milestones, incentivizing progress at critical stages.

Example: Alturix Energy faces an environmental compliance lawsuit with potential class action exposure. Pre/Dicta predicts a 42% likelihood of class certification and a 280-day timeline for the class certification phase. The firm structures a phased success fee, with higher bonuses at milestone completions like class certification denial. This phased arrangement aligns fees with key litigation phases and incentivizes strategic case management.

Deferred Fee Arrangement Based on Settlement Likelihood

Offer a deferred fee structure, where a portion of fees is delayed and tied to settlement outcomes, aligning fees with predicted case trajectory.

Example: VerdiGreen, an agriculture tech company in IP litigation, benefits from Pre/Dicta’s insights showing a 64% settlement likelihood within 312 days post-discovery. The firm agrees to defer a portion of fees until settlement, with a percentage of settlement proceeds supplementing the deferred amount. This allows VerdiGreen to manage cash flow while the case’s trajectory unfolds.

Value-Based Billing Tied to Judge Reassignment Analysis

Structure value-based fees adjusted based on the reassignment likelihood and tendencies of potential judges in the case.

Example: SkyFly Aviation, facing antitrust claims, uses Pre/Dicta’s predictions indicating a 73% early dismissal likelihood if filed in the Eastern District of New York, versus 24% in the District of Maryland. The firm sets a fixed fee if filed in E.D.N.Y, reflecting an early resolution likelihood. If the client wants to file in Maryland, a separate fee schedule applies to cover anticipated discovery, balancing costs with expected case demands.

Blended Fee with Outcome-Based Adjustments

Combine a fixed monthly retainer with outcome-based adjustments tied to settlement or trial, balancing risk for both client and firm.

Example: FFinBright Solutions, defending a consumer class action for data privacy breaches, sees a 77% likelihood of class certification and 39% dismissal likelihood post-certification according to Pre/Dicta. The firm offers a blended fee, with a retainer and outcome-based adjustments. A discount applies if the case settles in the first 10 months, while a premium success fee is added upon a favorable trial outcome or class decertification, aligning fees with case progress.

Performance-Based Firm Comparison for In-House Counsel

Equip in-house counsel with data-driven insights to compare law firms based on success rates and outcomes in specific case types, enhancing informed selection for optimal representation.

Example: GlobalTech Corp, preparing for a series of patent infringement claims, uses Pre/Dicta to compare law firms’ performance in defending similar cases. The analysis shows that Firm A has a 68% success rate in comparable cases, outperforming Firm B’s 49% rate. Armed with these insights, GlobalTech’s legal team selects Firm A, confident in their proven expertise in high-stakes patent litigation.

Data-Driven Differentiation for Competitive Advantage

Create predictive distinctions to highlight suitability for a particular matter or client.

Example: Klein & Johnson are preparing an RFP response for a large corporate client. Pre/Dicta provides a forward-looking analysis, projecting the firm’s success rate in the proposed matter compared to an aggregation of competitors. This comparative projection evaluates factors such as the nature of suit, jurisdiction, and historical outcomes to forecast Klein & Johnson’s likelihood of achieving a favorable result. The data reveals the firm’s superior performance potential in key areas like pre-trial motions and efficient case resolution. With these forward-looking insights, Klein & Johnson emphasize their projected advantage in the RFP, demonstrating their suitability for the client’s needs.

Predictive AI is revolutionizing the practice of litigation

We are neither a self-serve analytics tool nor a case law research vendor. We are providing next-generation litigation intelligence to practitioners and their in-house counterparts.

Motion to Dismiss

Predict outcomes with 85% accuracy.

Sharpen and elevate threshold motion practice with the most advanced litigation prediction technology available.

Motion Modeling

Forecast a variety of dispositive and procedural motions, including motions to compel, summary judgment, and class certification.

Mitigate risk, enhance leverage, and engage stakeholders with essential data-driven insights.

Timeline Predictions

Generate duration forecasts for every stage of litigation.

Maximize profitability and achieve greater budgetary certainty, all while ensuring client expectations remain clear.

Planning Assessments

Predictive comparisons of venues, courts, and judges.

Objectively assess venues in preparation for case filing, transfer motions, and peremptory challenges.

Improved motion practice. Increased client satisfaction. Better case outcomes.

Most firms continue to rely on anecdotal and imprecise means of forecasting litigation. Elite firms and sophisticated practitioners recognize there’s a better way.

Weight the probability of dispositive motion adjudication
Assess the downstream effects of venue selection, transfer, and reassignment
Use outcome and timeline forecasting to optimize settlement posture
Provision clients with actionable intelligence on litigation risk
Strengthen RFP responses with data-backed success predictions
Develop more accurate and competitive fee structures and budgets

Purpose-built for the modern attorney

Designed by a veteran litigator, Pre/Dicta is intuitive and accessible for modern attorneys – easily integrating into their daily workflows for smarter, faster decision-making.

Explore Pre/Dicta in a practical setting

Schedule a hands-on session with our team to learn how litigation forecasting works in practice and apply it to one of your firm’s cases.

Predict the course and outcome of litigation with proprietary legal intelligence

Forecast confidently with 85% model accuracy.

Predict the course and outcome of litigation with proprietary legal intelligence

Forecast confidently with 85% model accuracy.

A data-reinforced advantage for leading legal professionals

John B. Quinn

Predictive Case Intelligence

Predictive AI is revolutionizing the practice of litigation

Motion to Dismiss

Motion Modeling

Timeline Predictions

Planning Assessments

Improved motion practice. Increased client satisfaction. Better case outcomes.

Purpose-built for the modern attorney

Explore Pre/Dicta in a practical setting

ALM Legal Week's Innovator of the Year Award