# Pre/Dicta: Pre/Dicta \- Predictive Litigation Intelligence from Filing to Appeal

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## Pages
- [Platform](https://www.pre-dicta.com/platform/)
- [Pre/Dicta Video Introduction](https://www.pre-dicta.com/video-introduction/)
- [Homepage](https://www.pre-dicta.com/)
- [Contact](https://www.pre-dicta.com/contact-us/)
- [Platform\-old](https://www.pre-dicta.com/platform-old/)

## Posts
- [Integrating Machine Learning into Firm Workflow: Transforming Legal Strategy](https://www.pre-dicta.com/integrating-machine-learning-into-firm-workflow-transforming-legal-strategy/): Machine learning is redefining legal strategy by infusing empirical rigor into traditionally intuition\-driven decisions\. By analyzing decades of case data, judicial biographies, and procedural histories, ML tools uncover outcome patterns, forecast motions, and project timelines with unprecedented accuracy\.
- [Legal Practice Intelligence Features Pre/Dicta’s Expanded Capabilities](https://www.pre-dicta.com/legal-practice-intelligence-predicta-announcement/): The platform’s focus on augmenting instinct with empirically validated predictions aligns perfectly with LPI’s mission of advancing informed, data\-driven practice\.
- [Legal Tech Daily Showcases Pre/Dicta’s Expanded Predictive Platform](https://www.pre-dicta.com/legal-tech-daily-predicta-announcement/): The article highlights how Pre/Dicta’s expansion delivers new appellate forecasting capabilities, enhanced biographical intelligence, and comparative predictions across judges, venues, and law firms\. 
- [Charlie Uniman Highlights Pre/Dicta’s Latest Expansion in Legal Tech](https://www.pre-dicta.com/charlie-uniman-predicta-announcement/): Charlie Uniman, a seasoned lawyer turned legal tech startup evangelist, is among the first to share news of Pre/Dicta’s expanded platform\. 
- [Pre/Dicta Debuts Suite of New Capabilities, Further Expanding its Predictive Insights into Judicial Decision\-Making](https://www.pre-dicta.com/predicata-expands-predictive-judicial-intelligence/)

## research
- [The Selection of Disputes for Litigation](https://www.pre-dicta.com/research/the-selection-of-disputes-for-litigation/): A landmark article explaining why litigated cases are highly selected, producing balanced trial outcomes and revealing predictable filters in civil disputes\.
- [A general approach for predicting the behavior of the Supreme Court of the United States](https://www.pre-dicta.com/research/a-general-approach-for-predicting-the-behavior-of-the-supreme-court-of-the-united-states/): Using a time\-evolving random forest on nearly two centuries of Supreme Court data, this study shows that case outcomes and individual justice votes can be forecast with around 70% accuracy\.
- [Administrative Law Judges with Both High Dispositions and High Allowance Rates](https://www.pre-dicta.com/research/administrative-law-judges-with-both-high-dispositions-and-high-allowance-rates/): This OIG audit shows how a small group of high‑volume, high‑allowance SSA judges produced thousands of questionable disability awards and how targeted oversight reshaped their decision patterns\.
- [Chapter 11 Venue Choice by Large Public Companies](https://www.pre-dicta.com/research/chapter-11-venue-choice-by-large-public-companies/): This Federal Judicial Center study uses a national judge survey and detailed case data to show how large public companies choose Chapter 11 venues, why Delaware and S\.D\.N\.Y\. dominate, and how those choices actually affect creditors and case dynamics\.
- [The Supreme Court Forecasting Project: Legal and Political Science Approaches to Predicting Supreme Court Decisionmaking](https://www.pre-dicta.com/research/the-supreme-court-forecasting-project-legal-and-political-science-approaches-to-predicting-supreme-court-decisionmaking/): Using Rehnquist Court data, this study finds a transparent classification‑tree model can outpredict elite legal experts on Supreme Court case outcomes, mainly by better anticipating swing Justices’ votes\.

## Optional
- [Sitemap index](https://www.pre-dicta.com/sitemap_index.xml)