Abstract-Tuberculosis (TB) remains one of the leading health problems in the Philippines. Although curable, many Filipinos cannot afford the cost of treatment. Furthermore, the free services offered by the public health centers are insufficient to attend to the medical needs of those seeking help. In this paper, the researchers present the system that can assist doctors, nurses and health workers in diagnosing tuberculosis using techniques in machine learning through applying ID3 algorithm. Interviews with several experts in the field of TB were conducted in order to gather data that were used to populate the system's knowledge base. Test result show that the system is capable of prescribing treatments based on the patient's data and tracking the progress of the patient based on his/her prescribed treatment.