OBJECTIVES: Health authorities are keen to understand the clinical benefits and mortality reduction afforded by HPV vaccination for cervical cancer. Complex decision models are not always the most attractive nor the most appropriate means to highlight these benefits. The objective was to develop a relatively simple model to explore the population level impact of an HPV16/18 vaccine. METHODS: We developed a Monte Carlo model that estimated the absolute number of HPV infections, cervical cancer cases and deaths over the lifetime of a cohort of women. The model estimated the cancer cases and mortality avoided in the presence of vaccination (base-case: 75% vaccine uptake; 95% lifetime efficacy). RESULTS: Four countries were selected including Germany, Poland, Mexico and Taiwan. Each country has unique patterns of cervical cancer incidence, HPV-type prevalence and cervical cancer screening programs. The model predicted 4,584, 4,642, 4,162 and 37,935 cases of cervical cancer over the lifetime of unvaccinated 10 year-old girls in each of Poland, Germany, Taiwan and Mexico, respectively. Vaccination resulted in a reduction of total cervical cancer cases and deaths of 2,392 and 1,042 respectively in Poland; 2,423 and 857 in Germany; 2,143 and 930 in Taiwan and 16,780 and 8,381 in Mexico. Sensitivity analyses showed the most critical factors in maximizing the benefits of vaccination include vaccine uptake, efficacy, and duration of the protection. CONCLUSIONS: Monte Carlo simulation modeling can be a very powerful tool in understanding the potential benefits of vaccination against HPV infection for reducing cervical cancer and specific mortality.