A simulation model was developed to predict temperature and inactivation of E. coli O157:H7 and Salmonella during windrow composting. In particular, the model included an energy balance to estimate the change in temperature based on heat generated by biological decomposition and heat losses by convection, conduction, evaporation, and radiation. The model was validated with the measured data for the effects of seasonal variation on compost temperature and pathogen reduction. Sensitivity analysis was performed on the model to evaluate the variations in both seasons (winter and summer) and moisture contents (40% to 80%). The model showed the highest variation between experimental and predicted data only in winter composts. The results suggested that moisture content of 40% to 60% was appropriate for summer and 40% to < 60% for winter composting. Higher moisture levels did not demonstrate pathogen inactivation during winter conditions, whereas it took a month to eliminate the pathogens in summer according to the model predictions. Overall, the model was promising for evaluation of the composting process for different conditions. Further research is needed to improve the model predictions using measured process parameters under different environmental conditions.