Medicinal plants are sources of bioactive compounds for curing ailments since ages. In absence of modern analytical techniques during earlier period, characterization of plant bioactive metabolites was a difficult task, which has now become possible with the innovation in analytical methods. The emerging databases of medicinal plants rich in phytochemical data with bioinformatics and cheminformatics techniques have shown to be advantageous tools for drug discovery. Owing to rising trend of bioactivity databases, the practice of using computational tools for prediction of protein targets of small molecules has been showing advancement. Speedy progressions in computational technologies have significantly accelerated the development of computer-aided drug design. Recently, pharmaceutical sector has gradually shifted its attention towards traditional system of medicine for getting insight into novel lead compounds and directed their efforts towards 3D small molecular structure database available for molecular simulation or virtual screening. In this chapter an attempt has been made to discuss existing methods for target prediction based on the bioactivity information from the ligand side as well as the methods that are applicable in circumstances when the structure of a protein is known. The detailed account of in silico target identification applications based partly/whole on computational target predictions has been described.