According to the properties of cutting chatter, a new chatter forecast system has been developed based on Hidden Markov Model (HMM) and Support Vector Machine (SVM). This system uses HMM as the recognition method and SVM as the prediction method. At the same time, means like wavelet package decomposition are also employed to extract the cutting features. The basic idea and general steps of this method are as follow. Firstly, the cutting signals are analyzed step by step in the same interval using wavelet packet decomposition. Secondly, the energy in every spectrum section are calculated and scaled in order to get general property. As a result, the energy distribution information and energy transition curve of different spectrum section can be retrieved. Then, SVR algorithm is applied to predict the trend of energy transition. The results, after scalar quantized, at last are input into HMMs to determine whether in chatter period. Certainly, current state still needs to be distinguished. The simulation results indicate that the new predicting method has good discriminating performances and high forecast accuracy.