Considering the individual difference and infrequent action in actual operating accessories for the conventional circuit breaker, a realtime remaining mechanical life prediction method based on performance degradation model is proposed. Different from the traditional remaining useful life (RUL) prediction method, this method combines the historical degradation data of the operating accessories with the realtime condition monitoring (CM) data. Firstly, the linear and nonmonotonic degradation process of operating accessories is considered. A performance degradation model is formulated based on Wiener process. Secondly, the historical degradation data are utilized to determine the prior distribution of model parameters by the maximum likelihood estimation method and the onedimensional search method. Then, the Bayesian method is used to update the model parameters iteratively with the realtime CM data. Based on the concept of first hitting time, the RUL prediction model is formulated to realize the realtime prediction. Finally, the proposed method is evaluated by the life data of operating accessories. Experimental results show that the proposed method cannot only realize the realtime remaining mechanical life prediction of the operating accessories, but also has higher prediction accuracy than the methods utilized in other literatures.