Recent scientific advances are providing an opportunity to revisit strategies for cervical cancer prevention. How to invest health resources wisely, such that clinical benefits are maximized-and opportunity costs are minimized-is a critical question in the setting of new technology. In addition to an intervention's effectiveness, public health decision-making requires consideration of its feasibility, sustainability and affordability. No clinical trial or single cohort study will be able to simultaneously consider all of these components. A mathematical simulation model can be a useful tool with which to evaluate alternative cervical cancer control strategies by extending the knowledge from empirical studies to real-world situations. Models combine information about the natural history of disease with other relevant demographic, epidemiological, and economic characteristics. We describe a comprehensive Cervical Cancer Policy Model with a flexible structure that may be modified as new data on the biology of disease become available. This model provides an analytic framework to synthesize data on costs and benefits, to help design clinical guidelines, and to inform development of sound health policy. Examples of cost-effectiveness analyses conducted in the US and South Africa illustrate inevitable tradeoffs when choosing among a variety of interventions to decrease cervical cancer mortality, and demonstrate how these methods can facilitate a bridge between research and health policy.