Background <p>When comparing mortality, the severity of illness or injury should be considered; therefore, scoring systems that represent severity have been developed and used. Given that diagnosis codes in the International Classification of Disease (ICD) and vital signs are part of routine data used in medical care, a severity scoring system based on these routine data would allow for the comparison of severity-adjusted treatment outcomes without substantial additional efforts.</p> Methods <p>This study was based on the National Emergency Department Information System database of the Republic of Korea. Patients aged 15 years or older were included. Data from between 2016 and 2018 were used to develop the scoring system, and data from 2019 were used for testing. We calculated the products of the number of disease-specific survival probabilities (DSPs) to reflect the severity of the patients with multiple diagnoses. A logistic regression model was developed using DSPs, age, and physiological parameters to develop a more accurate mortality prediction model.</p> Results <p>The newly developed model showed predictive ability, as indicated by an area under the receiver-operating characteristic curve of 0.975 (95% CI: 0.974–0.977). When a threshold value of -5.869 was used for determining mortality, the overall accuracy was 0.958 (0.958–0.958).</p> Conclusion <p>We developed a scoring system based on ICD codes, age, and vital signs to predict the in-hospital mortality of emergency patients, and it achieved good performance. The scoring system would be useful for standardizing the severity of emergency patients and comparing treatment results.</p>