A sub-model describing persistence and efficacy of chlorothalonil fungicide was incorporated into a computer simulation model of Cercospora leafspot of peanut. The resultant model was validated using independent data sets from field trials over a two-year period. Predicted disease progress curves and area under the disease progress curve for different fungicide application schedules and rates were compared with field observations. The model was then used to compare predicted disease severity and area under the disease progress curve (AUDPC) for a calendar spray schedule vs a leafspot advisory program under different weather conditions. Predicted disease severity levels and area under disease progress curves were similar for advisory and calendar spray schedules. Results were insensitive to changes in parameters describing fungicide persistence or efficacy. The model described herein is a good estimator of the combined effects of weather and chlorothalonil treatments on disease progress, effectively ranks treatments or environmental conditions in terms of their effect on leafspot, and provides a basis for comparison of fungicide scheduling strategies. The simulation model predicted AUDPC more accurately than end-of-season disease, and AUDPC is a more reliable indicator of the effect of peanut leafspot disease on yield loss. Simulation experiments will be useful in optimizing fungicide or biocontrol strategies for long-term financial benefit to growers.