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Aiming at the problems of low data utilization and low prediction accuracy in the evaluation of the operation status of self-service baggage check-in equipment at airports, a method of equipment status evaluation combining Cox regression and Wiener process is proposed. First, build a sudden change model of equipment status under the influence of multiple risk factors based on event data, and build a gradual change model of equipment status based on the status data of key subsystems. A composite degradation index is proposed and the equipment performance degradation model is established based on the Wiener process to obtain equipment. The overall health status value and propose corresponding maintenance decisions. The experimental verification of the proposed method is carried out using the simulation data set of Commercial Modular Aero-Propulsion System Simulation and the operation monitoring data of self-service baggage check-in equipment. The results show that the equipment condition assessment method fusing Cox regression and Wiener process improves equipment data utilization and prediction accuracy.