INTRODUCTION: Anatomic injury, physiological derangement, age, and injury mechanism are well-founded predictors of trauma outcome. We aimed to develop and validate the first Scandinavian survival prediction model for trauma. METHODS: Eligible were patients admitted to Oslo University Hospital Ullevål within 24 h after injury with Injury Severity Score ≥ 10, proximal penetrating injuries or received by a trauma team. The derivation dataset comprised 5363 patients (August 2000 to July 2006); the validation dataset comprised 2517 patients (August 2006 to July 2008). Exclusion because of missing data was < 1%. Outcome was 30-day mortality. Logistic regression analysis incorporated fractional polynomial modelling and interaction effects. Model validation included a calibration plot, Hosmer-Lemeshow test and receiver operating characteristic (ROC) curves. RESULTS: The new survival prediction model included the anatomic New Injury Severity Score (NISS), Triage Revised Trauma Score (T-RTS, comprising Glascow Coma Scale score, respiratory rate, and systolic blood pressure), age, pre-injury co-morbidity scored according to the American Society of Anesthesiologists Physical Status Classification System (ASA-PS), and an interaction term. Fractional polynomial analysis supported treating NISS and T-RTS as linear functions and age as cubic. Model discrimination between survivors and non-survivors was excellent. Area (95% confidence interval) under the ROC curve was 0.966 (0.959-0.972) in the derivation and 0.946 (0.930-0.962) in the validation dataset. Overall, low mortality and skewed survival probability distribution invalidated model calibration using the Hosmer-Lemeshow test. CONCLUSIONS: The Norwegian survival prediction model in trauma (NORMIT) is a promising alternative to existing prediction models. External validation of the model in other trauma populations is warranted.