👉 Litigation math, often referred to as legal analytics or predictive analytics in the courtroom, involves using statistical and mathematical models to analyze legal data, predict outcomes, and inform strategic decisions. This approach leverages historical case data, legal precedents, and relevant variables (such as judge tendencies, case complexity, and evidence types) to estimate the likelihood of success for a particular claim or defense. By quantifying uncertainties and identifying patterns, litigators can make more informed decisions about case strategy, resource allocation, and even settlement offers. For instance, a well-calibrated model might predict a 70% chance of winning a complex patent infringement case based on similar past cases, guiding the litigator to allocate more resources to areas with higher potential success rates.
