Fuzzy logic is applied to the category discrimination problem related to identification of mammary lesions as benign or malignant. Results of other similar studies are reviewed. The current analysis expands the fuzzy logic approach by using the normal distribution function as set membership functions and using a genetic algorithm to optimize performance with the training partition. The approach is applicable to problems having arbitrarily large number of parameters. Two different data sets are examined. Data is portioned into a training set and validation set and each set are segregated into benign and malignant records.