<p>Modeling body vortex is essential for accurate missile aerodynamic prediction at high angles of attack, where separated flow dominates. This study investigates the impacts of body vortex on engineering-level missile aerodynamic prediction and compares the results with those of a semi-empirical vortex model. A vortex-tracking model based on two-dimensional potential flow is implemented in Missile DATCOM, with vortex strength and separation locations provided by an artificial neural network trained on body-alone CFD databases. The implemented method improves the prediction of local angle-of-attack changes near the body and yields more accurate nonlinear aerodynamic forces across body–fin and body–canard–tail configurations. Compared to the semi-empirical model, it better captures vortex interference, particularly for fins with low semispan. Notable improvements are observed in high angle-of-attack regimes and under roll control conditions.</p>