Abstract: Objective: To construct a prognosis prediction model for outpatient emergency acute lung injury(ALI)patients based on a logistic-Nomogram.Methods: A total of 308 ALI patients in Aviation General Hospital from March 2022 to January 2023 were selected.The prognosis of ALI patients admitted for 28 days was ana-lyzed, the clinical data of patients with different prognosis were compared, a Nomogram prediction model of poor prognosis was established based on the predictive factors by logistic analysis, and it was validated.Results: In the death group, age, positive end-expiratory pressure, pulmonary vascular resistance index (PVRI), acute physi-ology and chronic health status score system Ⅱ(APACHE Ⅱ) score, plasma high mobility group protein B1(HMGB1), monocyte chemoattractant protein-1 (MCP-1), soluble myeloid cell expression trigger receptor-1(sTREM-1), expression levels of serum miR-300 and miR-221, glucose-regulatory protein 78 (GRP78), chemo-kine receptor 4(CXCR4)and granulocyte colony-stimulating factor(G-CSF)were higher than those in the surviv-al group and the mean arterial pressure was lower than that in the survival group (all P< 0.05).Age, PVRI, APACHEⅡscore, plasma HMGB1, sTREM-1, MCP-1, expression levels of serum miR-300 and miR-221 and se-rum levels of GRP78, CXCR4 and G-CSF were all independent risk factors for poor prognosis in ALI patients(all P< 0.05).Based on the above factors, a Nomogram prediction model for ALI patients with poor prognosis was constructed.The area under receiver operating characteristics (ROC) curve (AUC) was 0.947, and the sensi-tivity and specificity were 91.45% and 86.53%, re-spectively.The calibration curve showed that the pre-dicted results of the model were in good agreement with the actual observation results.Conclusion: The prediction model based on age, APACHEⅡscore, HMGB1, sTREM-1, MCP-1, miR-300, miR-221, PVRI, GRP78, CXCR4 and G-CSF has good prediction efficiency for ALI.