Computational law has emerged as a novel paradigm from traditional legal studies in response to the revolution in information technology. Its evolution can be traced through several stages, including legal metrology, information retrieval, automated analysis, early expert systems, and, subsequently, the advent of network interconnectivity and artificial intelligence. This trajectory underscores the symbiotic relationship between computational law and technological advancements. The advent of next-generation generative artificial intelligence, exemplified by systems such as ChatGPT, presents new opportunities and challenges for computational law. A detailed analysis of generative AI capabilities in legal text processing, event analysis, and judicial decision support reveals that large-scale models exhibit potential in adjudication. Nevertheless, these models continue to face significant limitations in addressing complex legal scenarios, conducting precise fact-finding, and making sentencing determinations. In light of the future prospects of computational law and its practical constraints, this study proposes directions and recommendations for further development, with the aim of offering valuable insights into the field’s evolution.