The proposed system involves classification of X-ray images using both handcrafted visual features and deep learned features extracted from pre-trained CNN. 2Related Work A classification is a form of the data analysis process that extracts models describing important data classes. ...the histogram of the frequency of each integer occurring over the entire image is counted as 256-dimensional LBP descriptor. 6 proposed an approach where the automatic classification of medical X-ray images was performed using different feature extraction techniques such as Gray Level Co-occurrence Matrix (GLCM), Canny Edge Operator, Local Binary Pattern (LBP), pixel value as low-level image representation, and Bag of Words (BoW) as local patch-based image representation. Performance obtained was analysed regarding the image representation techniques used and results showed that LBP and BoW outperformed the other algorithms. 3Proposed Methodology In this proposed work, for classification of X-ray images two-level classification was performed. * In the first level, three different features were used for predicting the correct output. * By using those three predictions, the final prediction was done.