Abstract : In this research work we have developed a frame work for identification of class of hearing disorder using the decision bragged tree algorithm applied to the audio test reports dataset of people suffering from hearing impairments, The selection of machine algorithm was only done after understanding the nature of dataset , which was non linear and non separable dataset , since , the dataset of 60 tests, factor analysis was conducted to identify which parameters can help us design best discriminator for identification of hearing disorder class by doing we were able to implement the algorithm with high accuracy and low fraction of out of bag errors and margins errors.