OBJECTIVES: Chronic kidney disease (CKD) is a common and growing global health issue characterized by reduced glomerular filtration rate (GFR, mLs/min/1.73m2).  While investigators have used short-term changes in GFR as an endpoint, the relationship between this endpoint and long-term outcomes has not been reported.  The objective here was to estimate and quantify this relationship in order to predict the timing and number of cases of end-stage renal disease (ESRD) occurring over the lifetime of a cohort of hypothetical CKD patients with moderate and advanced disease. METHODS: We constructed a three-state Markov model (functioning kidney, ESRD, and death) with an annual cycle length to project GFR on long-term health outcomes. Using published GFR-specific risk equations, and adjusting for confounders, we estimated the probability of ESRD (assumed at GFR <10) and time to death according to baseline GFR categories defined by the United States (U.S.) Kidney Disease Outcomes Quality Initiative. Included in the modeling was a term representing two types of CKD patients characterized by “slow” and “fast” progression. RESULTS: For CKD patients aged 55 years, projected lifetime probabilities of progressing to ESRD were: 0.05, 0.25, 0.81, and 0.97 in GFR categories 45-59, 30-44, 15-29, and <15, respectively.  Projected mean survival times were: 16.7, 13.7, 11.4, and 9.4 years for the same GFR categories. The model was calibrated with mortality data reported by the U.S. Renal Data System. CONCLUSIONS:  The model can project the potential impact of baseline GFR on long-term outcomes in CKD. Estimating the time spent in GFR categories allows quantification of the entire trajectory of CKD until renal failure or death.  In future, the model may be refined by incorporating additional empirical data describing longer-term follow-up.