Biophysical models integrated with Decision Support Systems can be helpful tools for irrigation scheduling. The objectives of this study were (a) to evaluate the capability of the Cropping System Model (CSM)-CROPGRO-Cotton for simulating cotton growth and development under different irrigation scheduling regimes, and (b) to evaluate the potential of the (CSM)-CROPGRO-Cotton model as a tool for irrigation scheduling. Two experiments were conducted during the 2004 and 2005 growing seasons at the rainout shelters of the Griffin Campus of the University of Georgia. The (CSM)-CROPGRO-Cotton model was used to define the irrigation threshold (IT) treatments by estimating the timing of irrigation and the amount of water to apply. Each rainout shelter corresponded to one IT, which included 40%, 60%, and 90%. The irrigation event was triggered when the soil water content in the irrigation management depth dropped below the specified IT, e.g., for 40% IT irrigation was applied when water content in the soil dropped until 40% of the total soil water available. The model requires daily weather data, thus actual weather were used until the current date and the daily weather data of past 10 years were used to project the weather until the end of the growing season. The results indicate that the (CSM)-CROPGRO-Cotton model simulated cotton phenology, above-ground biomass, and yield fairly accurately for all irrigation treatments. The highest biomass and lint corresponded with the 60 and 90% IT. The 60% IT is one of the recommended irrigation practices, as it will conserve water compared to the 90% IT. The study also showed that the (CSM)-CROPGRO-Cotton model can be a promising tool for irrigation scheduling. However a variable irrigation management depth should be used and a correct characterization of the soil properties is needed. Further research includes the evaluation of the model for irrigation scheduling in farmers’ fields.