The pharmaceutical manufacturing process is complex and requires proper optimization to ensure that products are of consistent quality and efficiency and that they are in line with all regulations. A powerful statistical tool design of experiments (DoE) is an important part of process optimization, as it allows the analysis of the relationships between factors and responses in a systematic, logical manner. The given chapter is dedicated to the thorough application of the DoE to pharmaceutical manufacturing process optimization and begins with the basics of the tool, which include terms, concepts, and types. The chapter focuses on the application of the tool, and its major sections include identification of the critical parameters and quality attributes, building the design space, and running the experiments. The chapter offers technically thorough data analysis techniques, such as analysis of variance, regression analysis, and graphical data representation. The description of the chapter includes the details of the optimization strategies, process robustness testing, and implementation of the optimized conditions. The chapter provides a case study on the application of the discussed tool type in pharmaceutical manufacturing processes of tablet compression. It also reflects the view of the author on the specifics and future perspectives of the tool, including areas of concern and emerging trends. The major points and methods of tool implementation are summarized in the concluding section, where the view of the author on the efficiency and importance of the tool is described extensively.