Policy change and policy stasis happen constantly and lie at the fulcrum of politics and governance.   Both policy change and stasis are embedded in policy processes that involve various contexts, people, and events. While there have been hefty theorizing and empirical analysis on policy change and stasis dating back decades, there remains a gap in the literature about the mechanisms of change (e.g., change in resources, beliefs) and dynamics of change and stasis over long periods of time. The challenge is partly one of available data; it is difficult to develop datasets of policies, people, and events across many different contexts over time. This paper uses discrete event modeling, a tool used in industry and business to break down complicated systems into important and distinct decision points, as a potential means for addressing this limitation.  The purpose of the effort is to model causal mechanisms in coalition decision-making in reaction to random subsystem perturbations in order to explain coalition behavior and policy change and stasis, thereby simulating a part of the advocacy coalition framework – a major theoretical approach for understanding policy change. The simulation model is then discussed in relation to three case studies (U.S. watershed policy, U.S. foreign policy, Swedish Disaster policy). We conclude the presentation with a discussion of the possibilities of discrete event modeling to improve the theoretical understanding and future empirical research on the topic of policy change and stasis.