Abstract: Objective To explore the risk factors affecting the prognosis of sepsis patients progressing to chronic critical illness (CCI), and to construct and validate a Nomogram model for predicting in-hospital mortality risk. Methods Patients who met the criteria for sepsis progressing to CCI were selected from the Medical Information Mart for Intensive Care Ⅳ (MIMIC-Ⅳ) database in the United States as the research objects. Clinical materials of patients were collected retrospectively, and a total of 928 patients were included. The patients were randomly divided into modeling group (n=649) and validation group (n=279) at a ratio of 7 to 3; the patients were also divided into survival group and mortality group based on in-hospital mortality. Univariate and multivariate Logistic regression analyses were performed on the modeling group based on the outcomes; a Nomogram model for predicting in-hospital mortality in sepsis patients progressing to CCI was constructed based on independent risk factors; the discrimination and calibration of the Nomogram model were evaluated by the concordance index and calibration curve, and then validated by the validation group. Results Among the 928 sepsis patients progressing to CCI, 723 cases were in survival group and 205 cases in mortality group, with an in-hospital mortality rate of 22.1%. Age (OR=1.021, 95%CI, 1.007 to 1.036, P=0.004), body mass (OR=0.988, 95%CI, 0.979 to 0.997, P=0.016), the Acute Physiological Score Ⅲ (APS Ⅲ) score (OR=1.013, 95%CI, 1.004 to 1.023, P=0.004), blood alkaline phosphatase (OR=1.002, 95%CI, 1.000 to 1.003, P=0.023), continuous renal replacement therapy (CRRT) duration (OR=1.065, 95%CI, 1.023 to 1.108, P=0.002), and mechanical ventilation duration (OR=1.117, 95%CI, 1.056 to 1.184, P<0.001) were identified as independent influencing factors for in-hospital mortality in sepsis patients progressing to CCI. A prediction model was constructed based on these risk factors, and the concordance index analysis showed that the concordance index was 0.75 (95%CI, 0.70 to 0.80) in the modeling group and 0.74 (95%CI, 0.68 to 0.81) in the validation group. The calibration curves of both themodeling group and the validation group were close to the standard curve. Conclusion Nomogram model constructed based on the 6 indicators including age, body mass, blood alkaline phosphatase, APS Ⅲ score, CRRT, and mechanical ventilation duration has good discrimination and calibration for predicting the mortality risk of sepsis patients progressing to CCI, which is helpful for clinicians to assess patient's prognosis.