In this paper, combined with class interval estimation, a health assessment method for complex product components based on health index is proposed. Multiple monitoring parameters are transformed into single ones by establishing Mahalanobis distance (MD) time series. Furthermore, histograms are used to make distribution statistics on MD time series, and the results can be converted into health index to quantitatively evaluate the health status of complex product components. As for the selection of class interval, we use the closeness between the upper contour of histogram and the probability density function as the decision criterion. Finally, the method is validated by PHM08 data provided by NASA. The result shows that this method can effectively use the operational status data to assess the current health status of product components in time.