Continuous hidden semi-Markov model (CHSMM) is an extension of hidden Markov model (HMM), and it can be used to model time series process dynamically. It is capable of processing a new observation and modeling the time duration of hidden states by using a continuous observations density function and estimating the state duration parameters. In this paper, a model based on the CHSMM was constructed to assess the bearing performance degradation. First, the frequency band energy was extracted as the degradation indicators from the vibration signal. Second, the CHSMM was trained by the feature samples under normal conditions. Then, the test samples were input into this health assessment model, and their output probability was obtained. The difference between this probability and that of normal samples could be regarded as an index of degradation. Experiment results on the bearing performance degradation test indicated that, the proposed model can depict the degradation process effectively, and predict the occurrence of some incipient faults.