Abstract The traditional drug-discovery process that involves de novo design and validation of new chemical entity is a time consuming and expensive process. Even though there has been a many fold increase in the expenditure on drug discovery, the number of new chemical entities or new drugs approved remains considerably small. Accumulation and rational usage of high-throughput biological, clinical, and chemical data can accelerate the process of drug discovery. In silico drug design is a new paradigm that has a significant impact on the overall process of drug discovery. With the advent of innovative in silico drug-discovery techniques, researchers can integrate and mine a broad range of high-throughput biological data generated globally for drug repurposing, i.e., to find new indications for existing drugs. Drug repurposing, often termed as drug repositioning or drug reprofiling, has the considerable advantage of being comparatively much faster (~ 6 years) and more economical (~ 300 million dollars) than the traditional drug-discovery process. The integration of various in silico drug-discovery approaches like network-based, structure and ligand-based approaches, etc., has led to many instances of the successful repositioning of drugs. This chapter provides a comprehensive view of various in silico methods, their applicability, and the advantages and disadvantages for drug repurposing.