The study constructs a quantitative system of intelligent trial standards for civil and commercial cases using the network flow algorithm to optimize the problems of artificial intelligence in judicial trials. The construction of the system is centered on the minimum cost flow network. The feasible pairwise solution of the problem is solved by iteration, with the introduction of complementary slackness conditions. At the same time, arcs and nodes are added to the branches of the base feasible graph. These branches are then transformed into extended branches to improve the algorithm’s quantitative analysis of civil and commercial law cases. The intelligent trial standard quantitative system specifically includes five intelligent management functions: filing, file generation, proof and cross-examination, trial management, and sentencing recommendations. These functions are interconnected and work together to help the judicial trial process. The algorithm in this paper achieves a higher network link utilization rate, reaching 84.39% at 220 minutes. After applying the quantitative system of intelligent trial standards for cases, the judicial efficiency of Court A grew continuously between 2019 and 2024, with an annual growth rate of 3.624%. The average trial time for the three most frequent types of cases is in the range of 20.36 to 28.86 days, a substantial reduction compared to the time before the implementation of the system. In addition, the system in this paper can predict the best dispute resolution method for a case by measuring the peak of the factors related to the parties’ dispute resolution preferences.