Abstarct: Cancer remains one of the major challenges to public health worldwide, and its progression, particularly through tumor angiogenesis, is significantly influenced by the activation of the vascular endothelial growth factor receptor-2 (VEGFR-2), a receptor tyrosine kinase. VEGFR-2 plays a central role in endothelial cell proliferation, migration, and the formation of new blood vessels; therefore, its inhibition can effectively suppress tumor vascularization and mextastasis. In the present study, a series of reported bioactive derivatives were investigated to identify the molecular features governing VEGFR-2 inhibition and to facilitate the design of more potent anticancer agents. For this purpose, the three-dimensional structures of the compounds were generated and geometrically optimized, followed by the calculation of a comprehensive set of physicochemical, electronic, and spatial molecular descxriptors. After data preprocessing, feature selection was performed using the Adaptive Least Absolute Shrinkage and Selection Operator (ALASSO), resulting in the identification of the most influential descxriptors associated with biological activity. The selected descxriptors were subsequently employed for QSAR modeling using a feed-forward artificial neural network, leading to the development of the ALASSO–ANN model. Model evaluation demonstrated satisfactory predictive performance, with external test set R² and MSE values of 0.93 and 0.03, respectively. Furthermore, the Q_LOO^2 value of 0.83 confirmed the internal robustness and predictive capability of the developed model. In addition, molecular docking studies were conducted to investigate the binding interactions of the compounds within the active site of VEGFR-2 and to further validate the QSAR findings. Docking results revealed favorable interactions between the selected compounds and key amino acid residues located in the receptor binding pocket, suggesting strong inhibitory potential against VEGFR-2. Analysis of the selected descxriptors further indicated that electronic properties and spatial distribution parameters play dominant roles in determining VEGFR-2 inhibitory activity. Overall, the findings provide a reliable frxamework for the virtual screening and rational design of novel VEGFR-2 inhibitors and may contribute to the development of targeted anticancer therapeutics.