This paper proposes for a computer-aided tool to detect the severity of Tuberculosis (TB) in patients from their respective Chest X-ray (CXR) images. The collected dataset of CXRs with the respective severity is used to extract the feature matrix by valid medical observations and monitoring. This extracted feature matrix is further used to prepare the Back Propagation Neural Network in MATLAB using the MATLAB toolbox. The neural network thus created achieves an accuracy of 96% on using 12 hidden neurons and can be used to determine the severity of TB that is affecting the patient. The severity levels are: absent, mild, moderate, severe, and proliferate. This system can help the patients as well as the doctors with what further steps of treatment should be followed, and how prompt the further action needs to be. © Research India Publications.