Abstract: This paper designed a prediction model to effectively fit and predict the pantograph slide pan wear trend, which made up for the deficiency that the existing detection system could only detect the pantograph in real time. The paper used the linear support vector regression (SVR linear), least square support vector regression (LSSVR) and optimized least square support vector regression (MI-LSSVR) to train and fit the pantograph slide pan data obtained by the detection system, and used the model after training to predict the wear of the slide pan.The fitting accuracy of MILSSVR could reach 97.3%.In addition, the model could also be used to predict the thickness of the slide pan after the next operation in advance by using the mileage data of subway.When the slide pan was about to wear to the limit, the model could be used to predict the operating mileage that the slide pan could bear, reduce the workload of pantograph maintenance personnel, and improve the use efficiency of pantograph.