A substantial number of studies have employed Agent-Based Modeling (ABM) with particular theoretical considerations, frequently exhibiting a lack of rigorous empirical foundation. To ensure the empirical validity of ABM, Rand and Rust [128] propose four crucial procedures: micro-face validation, macro-face validation, empirical input validation, and empirical output validation. The latter two procedures are particularly demanding in terms of methodology. Empirical input validation involves the utilization of real-world data to specify the behavior of individual agents, while empirical output validation entails the comparison of simulation outcomes with corresponding actual data at the aggregate level. Based on such discussions, this chapter presents two studies conducted by the author to contribute to the empirical validation of ABM.