Computational drug discovery process is a challenging area that uses the contribution of multidisciplinary methods. The main purpose of computational drug discovery is to reduce the cost, time and laboratory experimental efforts associated with the identification of a new drug. One of the most used methods in different steps of computational drug discovery is pharmacophore modeling. A pharmacophore is a 3D model assigning the essential molecular features for the biological activity of a molecule. This chapter highlights the concept of the generation and using pharmacophore models in virtual screening and modern drug discovery research. Then, the most common concepts of pharmacophore model created based on either 3D structure of the target or ligand structures are explained. The major applications of pharmacophore models are virtual screening, molecular docking, and ADMET (absorption, distribution, metabolism, excretion, and toxicityAbsorption, distribution, metabolism, excretion, and toxicity (ADMET)) prediction. Especially, virtual screening, a computational technique that can use a pharmacophore model to search, is discussed more. Also, the chapter describes software for pharmacophore elucidation, from the 3D structures of ligand-protein complexes or from only ligands information. After building a pharmacophore model, 3D searches in large chemical or peptide databases can be done to retrieve potential active analogs with diverse scaffolds. This is of notable importance for pharmaceutical companies that need to discover novel lead molecules with better ADMETox properties and/or higher bioactivity towards the target. It should be noted that the advantages and limitations of the pharmacophore hypothesis are mentioned in this chapter.