NyayaMind- A Framework for Transparent Legal Reasoning and Judgment Prediction in the Indian Legal System
2026-04-10 • Computation and Language
Computation and LanguageArtificial IntelligenceMachine Learning
AI summaryⓘ
The authors created NyayaMind, a computer system to help predict court decisions in India and explain the reasoning behind them clearly. It works in two parts: one finds important laws and past cases, and the other uses specialized AI to reason and explain the decision step-by-step. Their tests show NyayaMind gives better explanations and matches evidence more closely than earlier systems. This makes it a useful tool for legal professionals needing transparent AI help with court cases.
Court Judgment PredictionLegal ExplanationIndian JudiciaryRetrieval-Augmented GenerationLarge Language ModelsLegal ReasoningPrecedent CasesStatutesAI in LawExplainable AI
Authors
Parjanya Aditya Shukla, Shubham Kumar Nigam, Debtanu Datta, Balaramamahanthi Deepak Patnaik, Noel Shallum, Pradeep Reddy Vanga, Saptarshi Ghosh, Arnab Bhattacharya
Abstract
Court Judgment Prediction and Explanation (CJPE) aims to predict a judicial decision and provide a legally grounded explanation for a given case based on the facts, legal issues, arguments, cited statutes, and relevant precedents. For such systems to be practically useful in judicial or legal research settings, they must not only achieve high predictive performance but also generate transparent and structured legal reasoning that aligns with established judicial practices. In this work, we present NyayaMind, an open-source framework designed to enable transparent and scalable legal reasoning for the Indian judiciary. The proposed framework integrates retrieval, reasoning, and verification mechanisms to emulate the structured decision-making process typically followed in courts. Specifically, NyayaMind consists of two main components: a Retrieval Module and a Prediction Module. The Retrieval Module employs a RAG pipeline to identify legally relevant statutes and precedent cases from large-scale legal corpora, while the Prediction Module utilizes reasoning-oriented LLMs fine-tuned for the Indian legal domain to generate structured outputs including issues, arguments, rationale, and the final decision. Our extensive results and expert evaluation demonstrate that NyayaMind significantly improves the quality of explanation and evidence alignment compared to existing CJPE approaches, providing a promising step toward trustworthy AI-assisted legal decision support systems.