Aimed at the problems that at present the anomaly detection and the residual useful lifetime (RUL) prediction exist in the integrated study, a RUL prediction model, i.e. a dynamic transition of the degradation model,is presented based on IMM algorithm. The presented model overcomes the disadvantages of the tradition models that the anomaly points at single stage are on no consideration by the prediction model, and can predict the RUL in real time. The numeric results show that the presented model can detect anomaly accurately, can reduce the uncertainty of RUL probability distribution, can improve the precision in RUL prediction, and can provide a basis for a decision making in completing maintenance work in accordance with the concret conditions.