The drug discovery and development is notably intricate, lengthy, and expensive. It often spans over a decade and incurs costs amounting to billions of dollars to introduce a new drug to the market. Nonetheless, an alternative strategy, computational drug repurposing, has recently garnered substantial attention. This pioneering approach seeks new therapeutic applications for existing drugs, thereby optimizing their utility and expediting the drug development timeline. This chapter examines the diverse data landscapes and advanced computational methodologies that are reshaping drug repurposing. We will investigate various techniques, including artificial intelligence–driven methods, knowledge graph–based approaches, profile-based repositioning, signature-based analyses, and structure-based and ligand-based strategies. These cutting-edge computational tools promise to reveal hidden therapeutic potentials and open up new possibilities for existing drugs.