This book presents a guide to integrating Knowledge-Based Engineering (KBE) with R for intelligent, data-driven engineering solutions. The book covers knowledge representation, rule-based systems, ontologies, predictive analytics, machine learning, optimization, simulation, and data visualization through practical R examples. Combining theoretical concepts with real-world case studies, programming exercises, and hands-on applications, it demonstrates how engineering knowledge can be automated and optimized to improve design, decision-making, and innovation. Intended for undergraduate and postgraduate students, researchers, educators, and practicing engineers, this book is a valuable resource for applying statistical computing and intelligent engineering techniques to solve complex multidisciplinary engineering challenges.