Toward Legal Reasoning Automation: Predicting Court Decisions with NLP and Deep Learning Approach

Innovations are essential to keep up with the swift changes occurring in both national and international legal frameworks. A developing field that combines law and technology is predictive justice, which utilizes deep learning (DL) and natural language processing (NLP) methods to forecast court rulings by analyzing legal data. This study examines recent predictive justice research and compares key areas where deep learning (DL) may be more suitable for modeling complex decision-making processes and those that require the extraction and analysis of large volumes of legal text using natural language processing (NLP). In this article, we present a feasible framework to aid in improving AI applications in law, utilizing specific metrics and their measurement processes across various legal contexts. From a practical perspective, we need to take a hard look at larger issues related to data privacy, ethical concerns, and the interpretability of AI models, which can increase transparency and equitable legal applications. This study is a valuable resource for academics and practitioners seeking to develop and utilize innovative predictive justice technology, as it combines strategies to achieve the state-of-the-art.