Urban mental health challenges call for new ways of designing policies to address the ongoing mental health issues in cities. Policymaking for mental health in cities is extremely difficult due to the complex nature of mental health, the structure of cities, and their multiple subsystems. This paper presents a general system dynamic model of factors affecting mental health and a method to test the sensitivity of the model to policy options using an approach combining system dynamics and fuzzy cognitive maps. The method is developed and tested to evaluate policies built around feedback loops. The approach succeeded in identifying the factors that substantially improve the mental health of the city population for specific contexts. It also suggests the coordination needed between different subsystems to reach these objectives.