Background: Immune checkpoint inhibitors (ICI) transformed treatment paradigm across cancers. There remain few reliable, clinically accessible predictors of ICI-induced immune related adverse events (irAEs). We derive a novel risk stratification model for irAEs using baseline patient, tumor and treatment variables in a large cohort of patients with advanced melanoma (AM) or non-small cell lung cancer (NSCLC) treated with ICI. Methods: We conducted a multi-centre retrospective observational cohort study of consecutive patients with AM or NSCLC receiving ≥ 1 cycle of single-agent or combination ICI, in any line, 2015 - 2023, in Alberta, Canada. Clinically significant irAEs, defined as those requiring treatment delay or systemic steroids/steroid sparing agents, were identified as outcome of interest. The association between irAEs, overall survival (OS), and time to next treatment (TTNT) was assessed with Cox Proportional Hazards regression. Stepwise logistic regression was used to select and weight baseline variables associated with development of irAEs to derive a predictive risk score. Model validation was carried out on 500 iterations of bootstrapped samples. Harrel’s C-index was calculated and internally validated to ascertain the model’s discriminatory performance. Results: 1,292 total patients were included, 519 (218/489 [44.6%] AM and 301/803 [37.5%] NSCLC) developing a clinically significant irAE. Using a subset of 801 patients with available baseline characteristics, the following variables were identified and weighted for creation of risk model (risk score attributed): tumor type (NSCLC) (+1), age >60 (+1), ECOG ≥1 (-1), BMI ≥ 25 (+1), ICI after first line (-1), combination ICI (+4), >10 cycles of ICI (+2), albumin level < LLN (+2), adrenal metastasis (+1), multiple sites of metastasis (-1). Patients were stratified into 3 irAE risk groups based on combined score: low (n = 230, risk score ≤ 0), intermediate (n = 412, risk score 1-2), high (n = 159, risk score ≥3). The risk model performed well with an optimism-corrected c-index of 0.707 in internal validation, and strong association with odds of irAE occurrence (Table). The development of irAE was associated with an improvement in OS (HR 0.48, 95% CI 0.41-0.44, p<0.001), with a median OS of 34.3 (95% CI 28.8-39.6) months compared to 12.0 (95% CI 10.6-14.3) months for those who did not develop an irAE. Similar robust stratification was also seen with TTNT. Conclusions: We presented and internally validated, a simple risk stratification tool that utilizes readily available baseline patient, tumor, and treatment characteristics to robustly stratify risk of irAE development.