Acetylcholinesterase (AChE) is a critical therapeutic target in the development of small-molecule inhibitors for Alzheimer’s disease (AD), a progressive neurodegenerative disorder characterized by cognitive decline and cholinergic dysfunction. In this work, 37 tadalafil analogs were studied as potential Acetylcholinesterase (AChE) inhibitors using a combined atom-based three-dimensional quantitative structure–activity relationship (3D-QSAR) modeling and molecular docking approach. Molecular docking studies were performed using the Glide program to predict binding affinity within the AChE active site and to validate key interactions responsible for inhibitory activity. The constructed 3D-QSAR model demonstrated excellent statistical robustness and predictive accuracy, showing a high correlation for the training set (R² = 0.975, SD = 0.190, F = 464.7, N = 29) and strong predictive performance for the test set (Q² = 0.809, Pearson(r) = 0.941, RMSE = 0.564 N = 8) using three partial least squares (PLS) factors. Analysis of the 3D-QSAR contour maps revealed critical structural regions where steric and electronic features either enhance or hinder Acetylcholinesterase (AChE) inhibition, providing valuable guidance for rational drug design. Based on these insights, five new candidate molecules were proposed, among which compound X1 exhibited the highest predicted inhibitory activity. These results highlight the power of integrating 3D-QSAR modeling with docking analysis to identify, design, and optimize potent Acetylcholinesterase (AChE) inhibitors, providing a strong foundation for the discovery of novel anti-Alzheimer’s agents.