Paper Key : IRJ************962
Author: Manish Thoke,Urvashi Ghore,Apurva Bhajan,Harsh Dongare,Prof. Mrs. Radhika Adki
Date Published: 02 Jan 2025
Abstract
Legal predictive analytics forcourt case judgment prediction is anemerging field that employs machinelearning (ML) and data mining techniquesto forecast legal outcomes. These modelscan anticipate case outcomes by analyzingprevious court cases, legal precedents, andother data to identify patterns and trends.The primary goal is aid legal practitionersby providing data-driven probabilities forvarious outcomes, hence improvingdecision-making and case preparationstrategies. Recent improvements in naturallanguage processing (NLP) have enabledmore effective parsing of complex legaldocuments, allowing models to deal withboth organized and unstructured data.However, significant obstacles remain,including data bias, ethical considerations,and the interpretability of machine learningmodels. Despite these limitations, thecreation of strong, explainable AI modelshas potential to improve legal analytics byenhancing transparency and efficiency.Thisstudy investigates the variousstrategies andmodels used in court case decisionprediction.
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