The peak of clamping force data of Metro doors can reflect the degradation of the transmission system to a certain extent. Based on this, this study uses the developed data acquisition system to collect, store, display, and query the clamping force of the new on-line metro door in real time. ARIMA model and EMD-ARIMA model are used to predict the trend of mean and standard deviation of peak clamping force with cumulative running time, and the probability of early failure of door transmission system is determined based on the prediction results. The comparison of the two models shows that EMD-ARIMA model can predict the change trend of peak clamping force of metro doors, and the improved prediction method can provide a new idea for predicting the deterioration of metro doors in debugging period.