This talk highlights the critical role of sex differences in mathematical oncology, demonstrating how biological sex influences glioblastoma biology, imaging biomarkers, treatment response, and predictive modeling. By integrating mathematical models, imaging, transcriptomics, and spatially resolved tumor data, sex-specific analyses improve the accuracy of precision medicine approaches. They further reveal distinct mechanisms underlying patient outcomes, emphasizing the need to incorporate sex as a fundamental biological variable in cancer research and clinical decision-making.