Legal professionals often grapple with the daunting task of efficiently accessing and comprehending extensive volumes of legal documents. To address this challenge, this chapter introduces an innovative approach that leverages optimization-based text summarization techniques for legal information retrieval. By systematically exploring legal corpora and implementing mathematical optimization-based text summarization algorithms, this study endeavors to enhance the efficiency and effectiveness of legal research. Ultimately, this approach aims to empower legal practitioners with improved capabilities to extract pertinent information from intricate legal documents. The efficacy of the proposed methodology is rigorously assessed using the FIRE 2019 AILA track’s dataset. The findings reveal a precision score ranging from 0.50 to 0.60, providing robust validation of the information retrieval system’s capacity to locate relevant statute law or prior case records essential for case inquiries.