We present a neural network application to the diagnosis of vocal and voice disorders. These disorders normally cause changes in the voice signal, so we use acoustic parameters extracted from the voice as inputs for the neural network. The selected neural network structure is Multilayer Feedforward. In this paper, we focus our application on the classification between pathologic and non-pathologic voices. The performance of the neural network is very good, 100 % correct in the test. Furthermore, having used neural network techniques to reduce the initial nuniber of inputs (35), we conclude that only two acoustic parameters are needed for the classification between normal and pathological voices. The application can be a very useful diagnostic tool because it is non-invasive, makes it possible to develop an automatic computer-based diagnosis system, reduces the cost and tirne of the diagnosis, is objective and can also be useful for evaluation of surgical, pharmacological and rehabilitation processes. Finally, we discuss the lirnitation of our work and possible future research.