The use of Bayesian statistics in psychology has been of recent focus. This paper discusses the effectiveness and usefulness of “Bayesian statistical modeling” in psychological studies by exploring its differences with traditional methodologies used in psychological studies. First, we explain differences between two trends in Bayesian statistics: hypothesis testing using Bayesian statistics and Bayesian statistical modeling. Second, Bayesian estimation and probabilistic programming languages may make it easy for psychologists to use statistical modeling. Third, the three advantages of studies using Bayesian statistical modeling in psychology are demonstrated. These advantages include developing mathematical explanations of behavioral mechanisms, valid estimation of psychological characteristics, and improved transparency and replicability of the data analysis. Fourth, it is argued that Bayesian statistical modeling and traditional psychological methodology could coexist by influencing each other.