Background: Infections are common complications in critical care, particularly in patients with severe multiple trauma, who are at elevated risk due to trauma-induced immunological changes. The heterogeneity of trauma patients complicates their initial assessment, yet timely recognition of patients at risk is crucial for guiding therapy and preventive measures. This study evaluated risk factors for sepsis and pneumonia in multiple trauma patients, incorporating a novel parameter: cell-derived extracellular particles (EPs) in plasma. Methods: Severely injured multiple trauma patients aged 18-80 years with an Injury Severity Score (ISS) ≥16 were included. Patient- and injury-related parameters were assessed at the injury site, admission and during clinical course. EP counts in plasma were measured at admission using intravesicular staining. Key variables from the first 24 h were analyzed to develop an early risk assessment score. Results: Among 124 patients, 16 developed pneumonia, and 29 developed sepsis. Pneumonia was associated with significantly lower Glasgow Coma Scale scores, higher intubation rates at the injury site and elevated Sequential Organ Failure Assessment scores at admission. Sepsis correlated with higher ISS, increased 24-h transfusion rates, lower leukocyte counts on day 1, and decreased levels of small EPs in plasma at admission. These variables formed the weighted Sepsis as Trauma Outcome Prediction (STOP) score. A STOP score >3 had a positive predictive value of 59.4% within 24 h upon admission to the emergency department for subsequent sepsis development. Conclusion: The risk of pneumonia in severely injured trauma patients was linked to impaired consciousness and preexisting organ-dysfunctions at admission. High-risk sepsis patients could be identified on day 1 following trauma using the STOP score, which incorporates ISS, 24-h transfusion rates, leukocyte counts at day 1, and small EP rates at admission. This novel scoring system could facilitate targeted therapeutic and preventive strategies for distinguishing high-risk populations.