This chapter introduces the methodological foundation for studying economic systems as dynamic, evolving entities. It critiques the limitations of static, equilibrium-based approaches and presents a flexible, interdisciplinary toolkit suited for the complexity of real-world economies. The chapter showcases how evolutionary economics benefits from methodological pluralism—combining qualitative depth, quantitative precision, simulation modeling, and historical insight. With the addition of a new section on prediction, it further explores how scenario-based modeling, probabilistic reasoning, and artificial intelligence can be integrated into evolutionary thinking. Rather than forecasting fixed outcomes, this approach emphasizes adaptive foresight—mapping possibilities, testing resilience, and modeling nonlinear system behavior. Throughout, readers are shown how methodological choices must align with the nature of the phenomena being studied, echoing the evolutionary principle that adaptation, not perfection, ensures survival. The chapter prepares the ground for concrete applications in innovation, policy, and institutional design explored in later chapters.