We present a modification to the Fuzzy ARTMAP neural network architecture for conducting classification in a probabilistic setting. We call this new architecture Hierarchical ARTMAP (HARTMAP). Performance comparisons with Fuzzy ARTMAP, Gaussian ARTMAP and Boosted ARTMAP on some simple two-class problems are discussed. Experimental results indicate that HARTMAP yields better generalization results on problems involving overlap of the underlying pattern distributions.