Technical Abstract: It is a common practice to grow winter wheat (Triticum aestivum L.) as a dual-purpose crop in the U.S. Southern Great Plains to capitalize added value by cattle production. Management of the dual-purpose wheat is complex because of the interactions and tradeoffs between grain and beef production. A wheat grazing model would be useful to optimize decision-making, but existing wheat growth models do not include grazing components. The objectives are to develop and incorporate a grazing and metabolizable energy-based cattle growth modules into the Decision Support Systems for Agrotechnology Transfer (DSSAT) model to simulate production of wheat grain and stocker cattle grazing on wheat during late fall and early spring. The wheat grazing model comprises of wheat growth, wheat-cattle interaction components, and cattle growth. Wheat growth is simulated by the wheat module of DSSAT. For wheat-cattle interface, individual leaf areas, as well as leaf, stem, and reserve weights and their corresponding N contents are adjusted for grazing on a daily basis. Cattle growth is based on a metabolizable energy balance. The model was applied to typical wheat-grazing scenarios. Results show that percent reductions of wheat grain yield are positively related to amounts of grazed biomass that is primarily a function of stocking rates and grazing duration. However, the percent reductions in grain yield are halved when the model is run with sufficient N addition, indicating additional N application is needed to compensate N removal by grazing. Daily weight gain per steer increases with grazing duration but decreases with stocking rates. Validation of the model against measured data will be reported in a separate paper. Field experiments are needed to quantify changes in wheat growth processes brought about by grazing for fine-tuning the wheat grazing model.