Fragment-based drug design (FBDD) has emerged as a powerful method for identifying lead compounds, offering significant advantages over traditional high-throughput screening (HTS). FBDD involves screening small, low-molecular-weight fragments (typically <300 Da) that exhibit weak binding affinities for their target proteins, followed by fragment optimization through chemical modifications. This approach, first popularized in 1996 by Shuker et al., effectively addresses the limitations of HTS, such as high costs and low hit rates. Over the past two decades, FBDD has led to the approval of several drugs by the U.S. Food and Drug Administration, including vemurafenib and venetoclax. The methodology involves a series of steps: constructing fragment libraries, fragment screening, and fragment optimization. Computational tools such as molecular docking and hotspot analysis play crucial roles in enhancing the efficiency of FBDD. This chapter outlines the fundamental principles, methodologies, and recent advancements in FBDD, with a focus on its applications in drug discovery and the integration of computational approaches to improve the identification and optimization of fragment hits. With its proven efficacy and increasing adoption by pharmaceutical companies, FBDD is positioned to play a pivotal role in the discovery of novel therapeutics for a wide range of diseases.