A new classifier was created by combining two existing models, naive-Bayes and finite-mixture, to improve classification accuracy and probability estimation. The new classifier uses a mixture model on the features of the naive Bayes model. Experimental results showed that the new classifier outperformed both the naive-Bayes and finite-mixture classifiers on real datasets.