Drugs achieve pharmacological actions for treatment by interacting with protein targets. Analyzing interactions of drug candidates or potential compounds with the therapeutic targets plays the most critical role in the drug discovery process. These interactions are based on various factors, including hydrogen bonds, charges, and lipophilic contacts. Pharmacophore models have become one of the computational approaches to describe these interaction patterns and facilitate the discovery process efficiently. In this way, it is possible to quickly identify promising primary hits that are highly efficient in large libraries. Metabolic diseases, also known as metabolic syndrome, are one of the world’s most pressing health concerns, affecting a considerable percentage of the global population. Metabolic diseases are a group of the body’s metabolic disorders of macronutrients such as proteins, fats, and carbohydrates. Genetic abnormalities can cause disorders in metabolism or may be acquired during one’s lifetime. Many members of metabolic syndrome (such as obesity, diabetes, hyperlipidemia, hypertension, or nonalcoholic fatty liver disease) are associated with wide-ranging molecular targets, and the discovery of their pharmacological agents becomes promising therapeutic trends. This chapter provides a general introduction of pharmacophore modeling and its roles in the drug discovery process. It showcases examples, highlighting the success of applying pharmacophore models in drug discovery for metabolic diseases at present and in future research.