OBJECTIVES: As HPV epidemiology and screening practices vary considerably and country-specific analyses are required to estimate the impact of vaccination against cervical cancer (CC), a health economic model based in Microsoft Excel was adapted to predict the long term clinic benefits of a prophylactic CC vaccination program, in addition to the present CC screening program for Chile. METHODS: A Markov model based on the natural history of HPV and cervical cancer was developed to simulate transitions between health states: normal, HPV infection, precancerous lesions, cervical cancer, and death. Using a lifetime simulation of 12-year old girls, the model was adapted for Chile-specific epidemiological endpoints: age-specific HPV prevalence, HPV type distribution in the general population, and age-specific CC incidence and mortality. The clinical impact of CC vaccination was assessed using the model calibrated for Chile. RESULTS: Oncogenic HPV prevalence in women (15-69 y.) was well matched overall (model predicted: 8.9%, reported: 9.1%). Similarly, using the present CC screening program features constant over time, overall number of CC cases and deaths were reasonably replicated (predicted: 762 cases and 436 deaths) during the follow up period. Considering that 62% of CC cases are associated to HPV-16/18 and cross-protection is as described for CC vaccines, the model forecasted that vaccination will reduce CC cases and deaths by 64.4% (762/436 to 271/155). Similarly, the vaccination program would reduce the number of precancerous lesions in 42.4% for CIN1 (52612 to 30301) and 64.4% for CIN2&3 (5998 to 2136). Sensitivity analysis showed that the clinical benefits described are most sensitive to changes in vaccine coverage, changes in the present status of the screening program and the prevalence of HPV-16/18 in invasive cervical cancer. CONCLUSION: Our model was successfully adapted to represent Chile epidemiological data and predicted a substantial long-term benefit of cervical cancer vaccination.