Speed limit policies are commonly adopted to manage and control traffic in urban areas due to their effectiveness and ease of implementation. Comprehending the complete effect of a speed limit policy is complicated and requires modeling and quantified investigations. In this paper, we propose a comprehensive simulation-based framework to assess the potential implications of different speed limit policies in urban residential areas. The framework models the policy impacts related to road safety (risk exposure for pedestrians and driving safety), traffic efficiency (travel time) and the environment (fuel consumption, exhaust emissions and noise exposure), using microscopic traffic simulation. The evaluations are conducted at various spatial granularity levels, i.e., link level, route level, origin–destination (OD) level and network level, and can be further utilized to develop relationship models between the key performance indicators (KPIs) and simulation inputs. The framework is implemented in an urban area located in the city center of Munich, Germany, and multiple speed limit scenarios are designed and compared. The results show that speed limit reduction can significantly improve road safety and environmental externalities within the modeled network/area with a relatively small cost to traffic efficiency. Such a framework can be used as an economical evidence collection method for an evidence-based policymaking approach to speed limit policies. The proposed simulation-based framework can also be further extended to adapt the assessment of other traffic-related policies.