A fast and effective method for classification of petroleum products based on Raman spectroscopy is proposed. A knowledge base composed by Raman spectra of training samples, intra-class feature spectra and intra-class thresholds of all classes was firstly established. Then, correlation coefficients between the test sample and the intra-class feature spectra were calculated. If the maximal correlation coefficient of the test sample is larger than or equal to the corresponding intra-class threshold, the test sample is determined to belong to the corresponding class. For 96 petroleum product samples belonging to 7 classes and 4 unknown samples, the experimental results show that this method can accurately classify known test samples and can also find the unknown test samples. This method costs little calculation time and human interference. Moreover, it can be easily implemented in the practical application.