Objectives: Parameters of patients' body composition have been suggested as prognostic markers in several clinical conditions including cancer and liver transplantation, but only limited data on its value in critical illness exist to date. In this study, we aimed at evaluating a potential prognostic value of the skeletal muscle mass and skeletal muscle myosteatosis of critically ill patients at admission to the ICU. Design: Exploratory observational cohort study. Setting: An urban, academic medical institution. Patients: One-hundred fifty-five patients treated for critical illness on a medical ICU. Interventions: None. Measurements and Main Results: We used routine CT scans to assess the patients' individual body composition. The skeletal muscle index as a surrogate for sarcopenia was defined as the total skeletal muscle area at the level of the third lumbar vertebra on axial CT scan, normalized for the patient's height. Myosteatosis was evaluated by assessing the mean skeletal muscle attenuation measured in Hounsfield unit at the same sectional plane. The skeletal muscle index and mean skeletal muscle attenuation at admission to the ICU were significantly higher in patients with long-term survival (180-day or 1-year mortality), while both parameters were comparable between short-term survivors and nonsurvivors (ICU mortality or 30-d mortality). Patients with a skeletal muscle index or mean skeletal muscle attenuation below our established ideal cutoff values (74.95 mm²/cm and 29 Hounsfield unit) showed a significantly reduced overall survival. These findings were confirmed in univariate and multivariate Cox regression analyses. Furthermore, myosteatosis significantly correlated with the time of mechanical ventilation, the duration of hospital stay, and the presence of sepsis. Conclusions: Our data suggest that sarcopenia and myosteatosis represent important prognostic factors in critically ill patients that can be easily obtained from routine CT scans. Both parameters at admission to the ICU yield important information on the patients' long-term outcome and might be used for early clinical decision-making in these patients.