Improving the accuracy of assigning new email messages to small folders can reduce the likelihood of users creating duplicate folders for some topics. In this paper we presented a hybrid classification model, PERC, and use the Enron Email Corpus to investigate the performance of kNN, SVM and PERC in a simulation of a real-time situation. Our results show that PERC is significantly better at assigning messages to small folders. The effects of different parameter settings for the classifiers are discussed.