OBJECTIVES: Recent legislation in Massachusetts promotes population health improvement while creating incentives to control healthcare costs.  This research creates a tool that projects population health in order to predict health care use and spending, and to help policy makers make decisions about the allocation of healthcare resources. METHODS: The Population Health Model is a micro-simulation that projects the health status and health care costs for Massachusetts residents over 50.  Drawing from the 1992-2010 Health and Retirement Study, we created modules for cancer, heart disease, COPD, diabetes, hypertension, stroke, and mortality risk using non-parametric survival analysis which adjusted for demographics, insurance status, smoking history, weight, and concurrent diseases. The model simulated individual health trajectories over 5 years based on the 2011 state subset of Behavioral Risk Factor Surveillance System data. RESULTS: The model projected that for the Massachusetts 2011 cohort, starting disease prevalence rates were 13.5% for diabetes, 42.9% for hypertension, 9.3% for heart disease, 10.6% for cancer, 8.2% for COPD, and 3.6% for stroke.  Over 5 years, projected incidence rates for this population were 37-40 per 1000 for hypertension, 22-26 for heart disease, 15-18 for diabetes, and 6-9 for cancer, COPD, and stroke.  The strongest predictors of disease onset were insurance status, behavioral risk factors, and comorbid conditions. CONCLUSIONS: The Population Health Model we developed is a health economic evaluation tool, which can predict future health outcomes for a cohort of Massachusetts residents over 50 based on their individual characteristics. The simulation results were validated using selected national datasets (US and Canada). Our next step is to predict healthcare costs over time based on the health status micro-simulation and information from both the Medical Expenditure Panel Survey and Massachusetts insurance claims data.