Deaths from tuberculosis have long gripped people and threatened human health. The need for new drug compounds are critically sensed by medical scientists and practitioners due to the emergence of new strains and the slow rate of discovering novel medicines for this disease. Since plants are a rich source of diverse drug compounds, they are among the best choices to achieve new ones. The study of all plants or their compounds is an almost impossible scenario; hence bio/cheminformatics methodology can be used to reduce time and cost spent in drug discovery. For this purpose, we made several databases of anti-mycobacterial plant compounds and further found filter criteria which were able to describe more predicted bioactive compounds by the established algorithm. Also, we present the survey of the developed resource by using bio/cheminformatics tools. The presence of several anti-mycobacterial compounds in the predicted algorithm and introduction of new active compounds represent the high potential of this method. In addition, the general profile of such bioactive molecules is pinpointed using molecular descriptors and cheminformatics approach.