In this paper, Bayes classifier method is used to analyze vibration signal from surface grinder and the finished quality is also monitored through process of grinding wheel spindle vibration. Based on Bayes classifier, the extraction of statistical parameters from the signal characteristics in the distribution of state values including waveform, peak value, margin value, skewness, and kurtosis is established to the training samples to calculate its covariance matrix which plays as classification tools for the establishment of the state of finished quality.Experimental results could be distinguished among the different states of finishing quality of grinding and classified into mirror, matte, chatter, scratch, and burning by using Bayes classifier method for their quality monitoring.