Deep Learning-Based Case Priority Prediction System for Smart Judicial Management in Indian Courts

Chouhan, Bhuvanshi

doi:https://doi.org/10.55041/ijcope.v2i5.816

Published on: May 2026

DEEP LEARNING-BASED CASE PRIORITY PREDICTION SYSTEM FOR SMART JUDICIAL MANAGEMENT IN INDIAN COURTS

Bhuvanshi Chouhan

Rakesh Verma

Department of Artificial Intelligence and Machine Learning Indore Institute of Science & Technology, Indore, Madhya Pradesh, India

DOI:https://doi.org/10.55041/ijcope.v2i5.816

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Abstract

The Indian judicial system faces a persistent and critical challenge: a massive backlog of pending cases exceeding five crore as of 2024, leading to prolonged delays in the dispensation of justice. This paper presents a Deep Learning-based Case Priority Prediction System—designated the Legal Ecosystem—that leverages Long Short-Term Memory (LSTM) neural networks and Natural Language Processing (NLP) to automatically classify and prioritize incoming legal cases into High, Medium, and Low urgency categories. The proposed system analyses structured case metadata (case type, filing date, urgency level, petitioner profile) alongside free-text legal descriptions to produce a priority score, which subsequently drives an intelligent hearing-date scheduling engine. The end-to-end architecture comprises a React/HTML frontend, a FastAPI middleware layer, a TensorFlow/Keras LSTM inference module, and a relational database backend. Extensive evaluation on a curated Indian legal case dataset demonstrates a classification accuracy of 99.1%, precision of 98.7%, recall of 99.4%, and macro F1-score of 99.0%. A comparative analysis against Random Forest, XGBoost, and Bi-LSTM baselines confirms the superiority of the proposed architecture. The system is designed with direct integration pathways to India's eCourts Phase-III infrastructure and the National Judicial Data Grid (NJDG), positioning it as a practical, scalable, and ethically grounded decision-support tool for judicial officers.

Keywords: Deep Learning; LSTM; Legal Text Classification; Judicial Decision Support; NLP; Case Priority Prediction; Indian Judiciary; eCourts; Smart Scheduling

How to Cite this Paper

Chouhan, B. (2026). Deep Learning-Based Case Priority Prediction System for Smart Judicial Management in Indian Courts. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(05). https://doi.org/10.55041/ijcope.v2i5.816

Chouhan, Bhuvanshi. "Deep Learning-Based Case Priority Prediction System for Smart Judicial Management in Indian Courts." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 05, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i5.816.

Chouhan, Bhuvanshi. "Deep Learning-Based Case Priority Prediction System for Smart Judicial Management in Indian Courts." International Journal of Creative and Open Research in Engineering and Management 02, no. 05 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i5.816.

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•Published on: May 29 2026

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