Legal Reforms for Addressing Prison Overcrowding

Abstract

Prison overcrowding remains a persistent challenge for criminal justice systems, particularly where prolonged undertrial detention, restrictive bail practices, procedural delay, economic disadvantage, and limited use of non-custodial sanctions interact.  This study examines prison overcrowding through a legalreform framework augmented by data-driven analytical methods capable of identifying structural drivers of excessive incarceration.  The research addresses a gap in existing scholarship by moving beyond isolated evaluation of bail or sentencing provisions and conceptualising decongestion as the combined outcome of multiple legal and institutional interventions. Particular attention is given to India's recent criminalprocedure reforms, including Section 479 of the Bharatiya Nagarik Suraksha Sanhita (BNSS), undertrial review mechanisms, legal-aid interventions, and financial assistance for prisoners unable to secure release because of poverty. A Legal Decongestion Intelligence Framework (LDIF) is proposed to integrate prison occupancy, undertrial duration, case characteristics, bail eligibility, legal-aid access, and institutional capacity indicators for reform assessment.The framework is designed to use interpretable machinelearning techniques to estimate overcrowding risk and simulate the likely aggregate effects of alternative reform scenarios without automating judicial decisions.