Since odor sensing system is required in many fields, we have developed the system using QCM (Quartz Crystal Microbalance) array and neural-network pattern recognition. Moreover, the system for measuring many samples by an automatic sampling stage has been developed. In the present study, the characterization of the sensing films deposited on QCMs was performed. Responses of 37 kinds of films exposed to 14 sorts of organic vapors were studied to classify sensing films and investigate sensor response models. As a result of the research, it was found that the similarities among films were obtained using principal component analysis, and the frequency shifts could be estimated using multiple regression analysis.