Summary: Naive Bayes is based on an assumption of conditional independence and the assumption can scarcely be satisfied. A weighted naive Bayes classification algorithm based on correlation coefficients is proposed. By computing correlation coefficients between condition attributes and decision attribute, different condition attributes are weighted differently. Thereby, the classification performance can be improved effectively and simply. With a new method offered first to solve the weights of attributes, on the basis of correlation coefficients it discusses the operation principle of the algorithm, as well as its implementation. Simulation results of traditional China medicine paediatric pneumonia case data set and a variety of UCI data sets verify the effectiveness of this algorithm.