BACKGROUND: We aimed to develop an actionable and feasible prospective clinical model to estimate toxicity risk to assist chimeric antigen receptor (CAR) T-cell therapy providers with the management of patients with relapsed and/or refractory large B-cell lymphoma. METHODS: We conducted an observational, retrospective cohort study using secondary data from 390 patients treated with the CD19 CAR T-cell therapy axicabtagene ciloleucel under two prospective clinical trials, ZUMA-1 and ZUMA-7; these clinical trials enrolled patients with relapsed/refractory large B-cell lymphoma between 2015 and 2019. Using machine learning and statistical methods, we developed a classification model for identifying patients unlikely to experience early cytokine release syndrome (CRS) and neurological events (NE) of any grade. RESULTS: We found the use of prophylactic corticosteroids to be an important factor in remaining CRS-free and NE-free within the first 3 days post-treatment (p<0.001). We identified a top model for no early CRS/NE using a set of six pre-lymphodepletion clinicopathologic features: number of lines of prior systemic therapy, age, baseline tumor burden (as measured by sum of the product of the diameters), C-reactive protein, aspartate transaminase, and hemoglobin, which achieves a positive predictive value of 0.71 in the holdout validation cohort. Additionally, we find that predicted probabilities generated from the model are strongly associated with incidence of Grade 2 or higher NE. CONCLUSIONS: We illustrated that routine clinicopathologic variables can be used to identify patients at low risk of developing early post-treatment CRS and/or NE. Such knowledge can be used to help treating centers prospectively manage patient care, including consideration of outpatient treatment.