Recently, the cheap-cost and the poor-quality of the foreign oolong teas have made to imitate Taiwan oolong tea or blend the low-quality foreign teas with Taiwan oolong teas, and sell it at high price; it results in a strong impact on Taiwan oolong teas’ industry. To assure the integrity of each producing area of oolong tea, 2-DE and nano-LC-MS/MS was applied to the comparative proteomics analysis of the teas with different production place, to find out the feature proteins as biomarkers for the certification of origins. In this study, 22 different product areas of oolong teas were used, the protein expression intensity measured by ImageMaster 2D Platinum. Further, we proposed a classification system, OTPS, for distinguishing the oolong teas product places. OTPS is based on K* with two layer feature selection mechanism of information gain and support vector machine. The classification accuracy of OTPS can reach 95.5%. Eventually, the 20 of feature proteins were analyzed with gene ontology found that the feature proteins were related with the growth environment and the stresses from tea processing. Consequently, this platform could be used in forecasting the produce places and gave each tea farmer a product resume; on the other hand, it is safer to consumers, and also decreases the dispute of commerce.