Background: Clinical decision support tools (CDSTs) can help physicians make complex treatment decisions and inform care. For colon cancer, CDSTs such as Adjuvant! Online and Numeracy were widely used to estimate the effects of adjuvant treatment and guide conversations with patients. Existing CDSTs, however, do not consider more contemporary predictive and prognostic factors, such as microsatellite instability (MSI), BRAF mutational status, or the presence of additional high risk clinical or pathological features (HRFs), in their assessment of outcomes. Current CDSTs are also not optimized for handheld devices. Methods: We developed ONCOPRE, which is an adjuvant chemotherapy benefit calculator for colon cancer that addresses the limitations of current CDSTs. Based on a comprehensive review of epidemiological data and results of landmark trials, ONCOPRE was devised to predict 5-year colon cancer recurrence and death. To validate ONCOPRE, we compared its predictions with those generated by existing CDSTs as well as real-world data from 7 tertiary cancer centers across Canada. Results: ONCOPRE is able to predict 5-year DFS and OS of patients with colon cancer based on age, sex, TNM status, and contemporary risk factors such as MSI status, BRAF mutations, and other HRFs. ONCOPRE’s predictions compare favorably with real-world data and predictions from other CDSTs. ONCOPRE’s predictions are typically more optimistic than historical outcomes, and this likely reflects the fact that current day colon cancer patients experience better prognosis with the use of modern therapy and improved supportive care. These attributes make ONCOPRE a potentially new benchmark among CDSTs that can reliably predict colon cancer outcomes. Conclusions: ONCOPRE (http://www.oncopre.com/beta/) represents a new CDST that can assist in adjuvant treatment decision-making and patient counseling. We make the case that the next generation of CDSTs in oncology must take into account more contemporary clinical, biochemical, and genetic risk factors since these elements significantly affect outcomes. The ONCOPRE platform serves as a potential model on which to develop prediction tools for other forms of cancers.