Legal Judgment

Legal judgment prediction research aims to leverage computational methods, primarily natural language processing (NLP) and machine learning (ML), to analyze legal texts and predict judicial outcomes or extract key information. Current research focuses on improving model accuracy and explainability using various architectures, including transformer-based models, and exploring techniques like prompt engineering and knowledge graph construction to enhance performance. This field holds significant potential for streamlining legal processes, improving efficiency in legal research, and offering valuable insights into judicial decision-making, though challenges remain in addressing biases and ensuring reliability.