Abstract: Association rules is a crucial problem in Knowledge Discovery in Databases（KDD）.Fuzzy association rules can be used to represent human knowledge in terms of natural language，and have recently received much attention from the KDD researcher.So far，however，most approaches of fuzzy association rules discovery are based on the measures of support and confidence for classical association rules.In fact，fuzzy association rules can be interpreted in different way，and the interpretation has a strong influence on the way of finding rules.From the logical point of view，fuzzy logic rules，support degree，implication degree and some related concepts are defined，and the algorithm of fuzzy logic rules discovery is proposed.This algorithm integrates the concepts of fuzzy logic and Apriori algorithm to find fuzzy logic rules from given quantitative databases.