In recent years, the theories of fuzzy systems and rough sets have been well developed respectively. In the paper, a combination of the two and its applications are presented. With the theory of rough set attribute reduction, unnecessary attributes are simplified based on old database. Relative memberships of new samples can be determined by fuzzy pattern recognition, which therefore result in less number of attributes for classification. Test examples show that this hybrid method can work reasonably and satisfactorily.