OBJECTIVES: To support decision making for health or social care policies and to improve access to medical innovations, population models (PM) have become a common tool that explicitly considers population dynamics. PM are applied for economic evaluations of specific treatments or public health interventions, predictions of demand for care or burden of disease. In our project DEXHELPP (Decision Support for Health Policy and Planning), we reconsider definitions of PM and focus on modelling techniques and methodological challenges. The goal of this systematic review is to increase the insight of health policy researchers in PM. METHODS: We performed a systematic review on PM, focusing on the development and application for health policy questions. We identified existing models, systematically extracted and summarized information in evidence tables and standardized narrative comparisons. We present goals, modelling techniques, general model characteristics/specifications, validation and advantages and shortcomings of chosen approaches. RESULTS: The term PM is not used consistently. It refers to both models applied to study the dynamics of a population and models investigating the impact of interventions on population level. PM consider open (dynamic) rather than closed cohorts. In general, populations can be projected into the future using micro- or macrosimulations, continuous or discrete time, and a modular structure allows studying several diseases and applications. Comprehensive PM are applied for several research questions, for example, in Canada (POHEM), Sweden (SESIM), Australia (APPSIM) or Austria (GEPOC) or by OECD/WHO (CDP). The identified models are often microsimulation models. Reported challenges are: data shortage, calibration, complexity and resource demands as well as quantifying uncertainty. CONCLUSIONS:  We identified several complex models with high quality, used for multiple research questions. The application of PM still requires better data, opportunities for data linkage and consistent reporting standards. Research should focus on continued methodological improvement for developing and applying complex population microsimulations.