The historical background of response surface methodology (RSM) traces its evolution from early experimental design principles to its widespread adoption in various industrial applications. This paper examines the development of experimental design techniques, initial approaches to optimization, and the statistical foundation underlying RSM. It explores the pioneering contributions of G. E. P. Box, who played a pivotal role in advancing RSM. The evolution of RSM terminology and its integration with computer technology are discussed, along with challenges and criticisms encountered over time. The cross-disciplinary adoption of RSM is highlighted, emphasizing its relevance across diverse fields. Modern developments and innovations in RSM are examined, including advancements in modeling techniques and optimization algorithms. The limitations of RSM, such as assumptions of polynomial models and sensitivity to initial experimental design, are acknowledged, with strategies proposed for overcoming these challenges. Overall, this abstract provides a comprehensive overview of the historical trajectory, industrial significance, and contemporary advancements of RSM, offering insights into its application and potential for future research.