The low-altitude economy refers to a comprehensive economic paradigm on airspace below 3,000 meters, utilizing aerial platforms such as unmanned aerial vehicles (UAVs) and electric vertical take-off and landing (eVTOL) aircraft, with broad applications in transportation, logistics, and inspection. eVTOLs offer advantages including electrification, vertical take-off and landing capability, low noise, and environmental sustainability, positioning them as a key solution for urban air mobility. In urban environments characterized by complex terrain, building-induced turbulence, wind shear, and vortex structures significantly perturb eVTOL aerodynamic performance, leading to lift fluctuations and reduced controllability. Particularly during take-off and landing phases, such flow disturbances increase the risk of instability, thereby imposing more stringent requirements on aerodynamic design and flight control system robustness. This study addresses the influence of vortex structures in complex airflow fields on the aerodynamic performance of aircraft by proposing an artificial neural network-based methodology for predicting such flowfield The investigation focuses on the 3D flow field along the descent trajectory of an aircraft under varying inflow conditions. The input features of the model include the inflow wind angle and velocity, while the output targets are the velocity components in the x, y, and z directions along the descent trajectory. This configuration creates a nonlinear mapping between the inflow conditions and the spatial velocity distribution. The network architecture is fine-tuned, and training parameters are optimized to improve convergence and generalization performance. Results indicate that the model effectively captures spatiotemporal variations in 3D velocity fields and accurately predicts velocity distributions at critical locations in the flow field under diverse conditions, with excellent approximation abilities, particularly in regions where vortex structures dominate. This data-driven approach offers viable potential for aerospace engineering applications.