Urban rail transit emergency plans are critical for managing operational disruptions, yet existing evaluation methods often suffer from subjective biases and non-quantifiable results. This study proposes a novel evaluation framework integrating the CRITIC method and cloud model theory to address these limitations. The CRITIC method objectively assigns weights to evaluation indicators by analyzing inter-criteria correlations and conflicts, while the cloud model translates qualitative assessments into quantitative representations using numerical features. An evaluation indicator system is established, encompassing comprehensiveness, operability, and cost-effectiveness. Case study results demonstrate that the comprehensive evaluation cloud aligns the emergency plan between “Average” and “Good,” highlighting its practical applicability despite areas for improvement. This method effectively reduces subjectivity, enhances visualization of results through cloud mapping, and provides a robust theoretical foundation for optimizing urban rail transit emergency preparedness.