The modified Trauma-Induced Coagulopathy Clinical Score (mTICCS) presents a new scoring system for the early detection of the need for a massive transfusion (MT). While validated in a large trauma cohort, the comparison of mTICCS to established scoring systems is missing. This study therefore validated the ability of six scoring systems to stratify patients at risk for an MT at an early stage after trauma. A dataset of severely injured patients (ISS ≥ 16) derived from the database of a level I trauma center (2010–2015) was used. Scoring systems assessed were Trauma-Associated Severe Hemorrhage (TASH) score, Prince of Wales Hospital (PWH) score, Larson score, Assessment of Blood Consumption (ABC) score, Emergency Transfusion Score (ETS), and mTICCS. Demographics, diagnostic data, mechanism of injury, injury pattern (graded by AIS), and outcome (length of stay, mortality) were analyzed. Scores were calculated, and the area under the receiver operating characteristic curves (AUCs) were evaluated. From the AUCs, the cut-off point with the best relationship of sensitivity-to-specificity was used to recalculate sensitivity, specificity, positive predictive values (PPV), and negative predictive values (NPV). A total of 479 patients were included; of those, blunt trauma occurred in 92.3% of patients. The mean age of patients was 49 ± 22 years with a mean ISS of 25 ± 29. The overall MT rate was 8.4% (n = 40). The TASH score had the highest overall accuracy as reflected by an AUC of 0.782 followed by the mTICCS (0.776). The ETS was the most sensitive (80%), whereas the TASH score had the highest specificity (82%) and the PWH score had the lowest (51.83%). At a cut-off > 5 points, the mTICCS score showed a sensitivity of 77.5% and a specificity of 74.03%. Compared to sophisticated systems, using a higher number of weighted variables, the newly developed mTICCS presents a useful tool to predict the need for an MT in a prehospital situation. This might accelerate the diagnosis of an MT in emergency situations. However, prospective validations are needed to improve the development process and use of scoring systems in the future.