To address the high risks faced by metro systems due to their enclosed underground spaces, vulnerable facilities, and structural complexity amidst frequent rainstorm waterlogging, it is imperative to develop a scientific vulnerability assessment method for metro stations to enhance comprehensive resilience. Based on the chain analysis framework of the driver-pressure-state-response-control (DPSRC) model, this study systematically analyzes the dynamic causality of metro rainstorm waterlogging risks and constructs an assessment index system comprising 5 criterion layers and 20 indicator layers. By integrating subjective and objective weights using the AHP-entropy weight method, a comprehensive vulnerability assessment approach for metro stations was proposed and applied to an empirical analysis of 99 stations in the Ningbo Metro. The results indicate that: ① The proposed method can accurately and effectively assess station vulnerability; ② Stations vulnerabilities exhibit an asymmetric distribution across high (19.10%), medium (51.69%), and low (29.21%) vulnerability levels, with 70.79% of stations exposed to risk, highlighting an urgent need for systemic prevention and control; ③ Waterlogging prevention capacity, monitoring and early warning capabilities, and emergency equipment reserves constitute the key contributing factors to high-vulnerability stations. This research provides a reference for rainstorm waterlogging risk management, disaster prevention, mitigation planning, and resilient transportation development in urban metro systems.