Using differential Raman spectroscopy and decision tree model, a classification model for identifying common shoe sole materials is established. This is a new method for identifying shoe sole materials. After preprocessing the pre-spectrum, the samples are classified according to the main components of the shoe sole, and then principal component and hierarchical clustering analyses are used to verify the classification results. Based on the classification results, a classification tree model is established, and finally 51 samples are recognized and classified with overall classification accuracy of 98.0% and the accuracy is 84.3% after cross-validation. These results show that using differential Raman spectroscopy and decision tree model can realize a more accurate identification and classification of shoe sole sample spectrum, providing a certain reference for the differentiation and identification of other physical evidence.