Mathematical modeling has proven to be an effective method for studying glucose homeostasis. Over the last several decades, quantitative models have provided critical insights into the complex regulatory mechanisms underlying optimal blood glucose control. This review summarizes significant advances in elucidating the dynamic glucose-insulin relationship from the molecular to the organismal levels using mathematical representations. We show how early conceptual models paved the way for increasingly sophisticated multi-scale computational models. We also talk about how the ongoing collaboration between modeling and experiments helps us understand glucose homeostasis and drives therapeutic innovation. Finally, we discuss new frontiers such as integrating glucose regulation into whole-body regulatory networks and unraveling long-term compensatory mechanisms.