Breast cancer is a complicated type of cancer that mainly occurs in women and poses a global challenge due to its genetic diversity, making accurate diagnosis challenging. The accepted approaches are categorized based on cancer subtype and metastasis level. This study focuses on a predictive drug discovery strategy for compounds that may modulate interaction with HER-2 and EGFR, two important receptors in cancer treatment. We employed a 3D QSAR methodology, complemented by molecular docking, ADMET analysis, and molecular dynamics simulations, to evaluate the antiproliferative effects of pyrazole-benzimidazole derivatives on MCF-7 cells as targeted therapies. External validation confirmed the predictive accuracy of the generated models. The best CoMSIA (Comparative Molecular Similarity Indices Analysis) and CoMFA (Comparative Molecular Field Analysis) models exhibited significant Q