Lex Machina is a legal analytics platform that helps litigators predict how judges, opposing counsel, and case types are likely to behave based on historical court data. The project began in 2006 as a public-interest effort at Stanford Law School under Professor Mark Lemley, incorporated as a company in 2008, and was acquired by LexisNexis in 2015, where it now operates as a dedicated product line.
The platform mines millions of federal and state court filings, judgments, and case outcomes to surface patterns, such as how a specific judge tends to rule on a motion type or how long a case type tends to take to resolve, and has since expanded into practice areas including patent, class action, and other IP litigation. Its Class Action Module, for example, adds analytics across more than 140,000 cases.
Lex Machina serves litigators, in-house counsel, and law firms building case strategy or evaluating outside counsel performance before committing to a lawsuit. Pricing is not published; annual subscriptions are quoted per firm and reportedly range from several thousand to tens of thousands of dollars depending on firm size and case volume.
