Fuzzy neural network is an artificial neural network that combines fuzzy concepts, fuzzy inference rule with structure and learning ability of neural network. Clustering is an important tool in data mining and knowledge discovery. Fuzzy ART (Fuzzy Adaptive Resonance Theory) is a fuzzy neural network that solves effectively clustering problem. Fuzzy ART clusters better than traditional methods based on three following advantages: Learning data until satisfying a given conddition, creating a new category without affecting to existing categories, and easily choosing parameters of Fuzzy ART. In this papper, the authors apply Fuzzy ART for clustering 5 brenchmark datasets. After showing results of experiments, the authors present guide to choose suitable values for parameters of Fuzzy ART that the ability of clustering is the highest. Then, the authors analysis the advantages of Fuzzy ART when it is applied to clustering data. Results from experiments also show that Fuzzy ART cluster much effectively for clustering problems.