Lipstick is considered to be one of the most important physical evidence in forensic science. In order to establish a new method for detecting lipsticks, 50 lipstick samples are tested by using differential Raman spectroscopy combined with chemometrics method. It can be observed from the differential Raman spectrum that the lipstick contains various oils, waxes and oxides. By analyzing the spectrum, lipstick samples of different brands and different series of the same brand can be distinguished according to one or more Raman characteristic peaks, and the discrimination power (DP) value is 100%. All samples are reasonably divided into 10 categories by cluster analysis method, and the DP value is 88.16%. The classification model based on cluster analysis is established by distance discriminant method, the classification accuracy rate can reach 96.00% after cross-validation. The results show that the proposed method can realize non-destructive inspection, and the collected spectra have high signal-to-noise ratio and are not disturbed by fluorescence.