Cervical cancer is a global health issue, and developing countries bear the highest death rates. Though, cervical cancer etiology is well understood and prevention is possible. Both vaccines and effective screening tests exist, which can significantly reduce incidence. While designing cost-effective public health policies is of paramount importance in countries with limited resource availability, it requires an ability to generate reliable long-term predictions about the dynamics of a population health state, a task that entails significant complexity. This poster presents a simulation-based computational tool that can assist decision-makers in shaping national public health policies.