BACKGROUND: Reliable prognostic markers for predicting severity of allergic reactions during oral food challenges (OFC) have not been established. OBJECTIVE: We sought to develop a predictive algorithm of a food challenge severity score (CSS) to identify those at higher risk for severe reactions to a standardized peanut OFC. METHODS: Medical history and allergy tests were obtained for 120 peanut-allergic participants who underwent double-blind, placebo-controlled food challenges (DBPCFCs). Reactions were assigned a CSS between 1 to 6 based on cumulative tolerated dose and a "severity clinical indicator." Demographic characteristics, clinical features, peanut component IgE values, and a basophil activation marker were considered in a multi-step analysis to derive a flexible decision rule to understand risk during peanut of OFC. RESULTS: 18.3% participants had a severe reaction (CSS >4). The decision rule identified the following three variables (in order of importance) as predictors of reaction severity: ratio of %CD63hi stimulation with peanut to %CD63hi anti-IgE (CD63 ratio), history of exercise-induced asthma, and forced expiratory volume in 1 sec/forced vital capacity (FEV1/FVC) ratio. The CD63 ratio alone was a strong predictor of CSS (p<0.001). CONCLUSION: The CSS is a novel tool that combines dose thresholds and allergic reactions to understand risks associated with peanut OFCs. Lab-values (CD63 ratio), along with clinical variables (exercise-induced asthma and FEV1/FVC ratio) contribute to the predictive ability of the severity of reaction to peanut OFC. Further testing of this decision rule is needed in a larger external data source before it can be considered outside of research settings.