To systematically investigate the vertical uplift capacity of helical anchors in aeolian sand and establish a predictive model, this study employed an integrated approach combining in-situ tests, numerical simulation, and machine learning. The results of in-situ tests and numerical simulations were compared and validated, deeply revealing the uplift bearing mechanism of helical anchors and systematically analyzing the influence of key parameters such as helix diameter, spacing, and embedment depth on the bearing behavior. Furthermore, a dataset generated from numerical simulations was used to train machine learning models, identifying the most influential parameters on the uplift capacity. These parameters were then used as variables to formulate a predictive equation by fitting the relationship between the uplift capacity factor (N_qu) and the lateral earth pressure coefficient (K_u). The results indicate that the uplift load-displacement response undergoes a transition from linear to nonlinear, and then to a near-linear hardening phase. The uplift capacity increases exponentially with the helix diameter but shows a limited correlation with the number of helices. The critical value for deep and shallow embedment of helix anchors was determined to be 5D （D is plate diameter）, revealing that the transition between cylindrical shear failure and individual plate failure in multi-helix anchors occurs at a helix spacing of 4D~5D. A theoretical formula for calculating N_qu in relation to K_u for helical anchors in aeolian sand was proposed. Validation against field test results showed a deviation within 5%, demonstrating high prediction accuracy and stability. The findings of this research provide significant technical support for the refinement of design theories and the practical application of helical anchor foundations in sandy soil regions.