From the perspective of the future development of maglev transportation, establishing a prediction model that correlates the degradation characteristics of maglev systems, which are subject to long-term physical weathering and operational structure deterioration, with service time, speed, and other factors, is a technical means and monitoring method for effectively responding to natural disasters and operational safety warnings. This paper, based on the characteristics of high-speed maglev rail-clamping operation, combines “spatiotemporal” data analysis to examine the impact of performance degradation parameters at multiple time scales on the intrinsic mechanism model of the high-speed maglev vehicle-magnetic-rail system. Utilizing digital twin technology to simulate the operation of maglev trains, a hybrid-driven high-speed maglev vehicle-magnetic-rail model considering the effects of degradation is established at multiple spatiotemporal scales, integrating data and mechanism. The accuracy of the aforementioned hybrid model is verified using actual measurement data. This resolves the operational stability and safety issues of the vehicle and track systems as their performance parameters deteriorate over time.