BACKGROUND: The Norwegian Survival Prediction Model in Trauma (NORMIT) is a newly developed outcome prediction model for patients with trauma. We aimed to compare the novel NORMIT to the more commonly used Trauma and Injury Severity Score (TRISS) in Finnish trauma patients. METHODS: We performed a retrospective open-cohort study, using the trauma registry of Helsinki university hospital's trauma unit, including severely injured patients (new injury severity score > 15) admitted from 2007 to 2011. We used 30-day in-hospital mortality as the primary outcome, and discharge functional outcome as a secondary outcome of interest. Model performance was evaluated by comparing discrimination (by area under the receiver operating characteristic curve [AUC]), using a re-sample bootstrap technique, and by assessing calibration (GiViTI belt). RESULTS: We identified 1111 patients fulfilling the study inclusion criteria. Overall mortality was 13% (n = 147). NORMIT showed slightly better discrimination for mortality prediction (AUC = 0.83, 95% confidence interval [CI] = 0.80-0.86 vs. AUC = 0.79, 95% CI = 0.75-0.83, P = 0.004) and functional outcome prediction (AUC = 0.78, 95% CI = 0.76-0.82 vs. AUC = 0.75, 95% CI = 0.72-0.78, P < 0.001) than TRISS. Calibration testing revealed poor calibration for both NORMIT and TRISS (P < 0.001), by giving too pessimistic predictions (predicted survival significantly lower than actual survival). CONCLUSION: NORMIT and TRISS showed good discrimination, but poor calibration, in this mixed cohort of severely injured trauma patients from Southern Finland. We found NORMIT to be a feasible alternative to TRISS for trauma patient outcome prediction, but trauma prediction models with improved calibration are needed.