In order to evaluate the testing indicators of transportation equipment better, this paper proposes an evaluation method for transportation equipment testing indicators addressing advancement, economy, technical maturity, and foresight, which incorporates 20 primary and 74 secondary indicators, providing a comprehensive framework for assessing testing methods. To achieve scientific and reasonable optimization, an improved information sensitivity analysis model was proposed to optimize the indicators, ensuring the retention of the most representative 32 indicators while reducing informational redundancy. This approach enhances the accuracy and reliability of the evaluation, surpassing traditional methods like principal component analysis. The findings emphasize the critical factors influencing testing methods, including test point representativeness, environmental stability, cost-effectiveness, and adaptability. The proposed method not only supports current testing improvements but also offers significant scalability and practical guidance, contributing to the technological advancement and standardization in railway equipment testing. This research provides valuable insights into optimizing evaluation frameworks for complex testing requirements in the railway industry.