OBJECTIVES: To develop a framework to model progression of Parkinson’s Disease (PD) for early economic evaluation of disease-modifying therapies. METHODS: A patient-level time-to-event simulation was designed to model disease progression of PD, comparing a hypothetical disease-modifying treatment to current standard of care (SOC). The model was conceptualized based on literature, treatment guidelines, and statistical analyses of the Parkinson's Progression Markers Initiative (PPMI) study (N=423, baseline mean age 61.7 years, not on dopaminergic therapy [DT], disease duration 6.6 months, 6 years follow up) and the National Institute of Neurological Disorders and Stroke Exploratory Trials in PD Long-Term Study 1 (NET-PD-LS-1; N=1,720, baseline mean age = 61.8 years, on DT, disease duration 18.5 months, 6 years follow-up). Equations to predict progression of MDS-UPDRS parts I-IV for patients not on DT were derived from PPMI, and to predict progression of UPDRS parts I-IV following DT initiation were derived from NET-PD-LS-1. Published equations were used to map UPDRS to MDS-UPDRS, and PPMI data was used to map MDS-UPDRS III to Hoen and Yahr (HY) stage. Following progression to HY III, HY stage progression was modeled using published transition rates. RESULTS: Predictors of MDS-UPDRS progression included age, gender, disease duration, DT use, and prior MDS-UPDRS subscores, and predictors of UPDRS progression included age, gender, disease duration, off-time, levodopa-equivalent daily dose, and prior UPDRS subscores. Mean baseline values of MDS-UPDRS I, II, III, and IV were 5.8, 6.1, 21.6, and 0, respectively. Simulation using the PPMI-based equations prior to DT and NET-PD-LS-1-based equations following DT predicted a six-year change in MDS-UPDRS I, II, III, and IV scores of 4.2, 7.1, 10.0, and 1.5. CONCLUSIONS: This new framework can be further enhanced and used to project the long-term outcomes of PD and could be used for evaluation of cost-effectiveness of disease-modifying therapies currently being studied.