With the advance of intelligent operation and maintenance in china railways, the requirement of condition monitoring and remaining life prediction for lightning protection equipment has become increasingly urgent. MOV(Metal Oxide Varistor) is the key component of railway surge protector, and it is necessary to study the description model of its degradation process. The output of the model that uses a single parameter to characterize degradation is more prone to contingency, and cannot truly and fully reflect the life state of the MOV. The degradation of MOV is a cumulative effect, and its life model should consider the surge history information. In view of the above problems, a prediction model of the residual life value of MOV is given by combining various degradation related parameters and surge history. Firstly, nine degradation related parameters are fused to construct degradation core. Then, the degradation core and surge history are fused through Markov chain to build a life model of MOV. Then, the model is calibrated with experimental data. Finally, the model is validated and analyzed by experiments. The model can describe the degradation process of MOV more comprehensively and accurately, and can predict the residual life value at the same time, and it has potential application in the life assessment of surge protective devices.