Pollen-mediated gene flow from genetically modified plants to non-target plants is a concern of crop growers, seed companies, the general public, and the scientific communities. Although there have been descriptive and mechanistic models to describe pollen dispersion, there has rarely been a comprehensive mechanistic model to dynamically simulate pollen release, dispersion, and deposition and to finally relate them to the gene flow (outcrossing). This research developed and validated such a comprehensive mechanistic model for corn crop gene flow risk management. Dynamic pollen dispersion and deposition were predicted by a 3-D random walk model according to inputs of weather data and plant and domain characteristics. Actual gene flow (outcrossing ratio) was obtained according to predicted grand total deposition flux at silk height during the whole pollination season. The model was validated by experimental data and was appropriate to predict gene flow with acceptable accuracy under different atmospheric and environmental conditions; on average, the ratios of measured and simulated values ranged from 0.82 to 1.21, while R2 ranged from 0.56 to 0.68. The model can be easily adapted for other genetically modified crops.