The integration of advanced mathematical and computational methodologies is playing an increasingly central role in cancer research, offering critical insights connecting biological mechanisms to clinical applications and predictive models that guide clinical decision-making. This growing interest underpins the emergence of Mathematical Oncology—a multidisciplinary field dedicated to understanding tumor dynamics and optimizing therapeutic strategies through mathematical modeling and computational simulation. The field’s expansion is also reflected in the widespread engagement with platforms such as The Mathematical Oncology website and newsletter, which currently reach over 2,300 subscribers within the scientific community. Yet, the highly interdisciplinary nature of the discipline makes it difficult to have a comprehensive overview of the evolution of the area, and of the different research lines shaping its development. In this study, we address this gap through a comprehensive bibliometric analysis of over 19,000 citable documents across 75 years, and a comparative analysis of hand-curated publications list from 7 years of the Math Onco newsletter. In the analysis, we review the number and type of publications, the impact and topical focus of common journals, common modeling methods over time, the most studied disease sites, and a geographical analysis of institutions involved. Finally, we perform a citation network analysis of the highly productive authors (by total publications) and then illustrate a clustering analysis to group the field into subsections based on disease, modeling methods, and target journals.