Objective: To analyze the influencing factors of disease outcome in patients with extensively drug-resistant Acinetobacter baumannii (XDR-AB) pulmonary infection, and construct a Logistic regression prediction model, so as to provide reference for early prediction and development of prevention measures in clinical practices. Methods: A total of 120 patients with XDR-AB pulmonary infection admitted to the hospital from February 2017 to December 2020 were selected as the research objects. Information of patients such as gender, age, diagnosis, complication, length of stay, medication, examination index, and outcome were collected, the influencing factors of disease outcome were analyzed and a Logistic regression prediction model was constructed. Results: Among 120 patients with XDR-AB pulmonary infection, 68 survived (56.67%) and 52 died (43.33%) after treatment. Univariate analysis showed that the rate of admission to ICU, rate of combined cardiac insufficiency, rate of combined respiratory failure, rate of combined use of antifungal drugs, rate of use of antibacterial drugs for less than 6 days, rate of use of noninvasive ventilator, rate of invasive ventilation, rate of indwelling gastric tube and rate of the highest body temperature (below 38.6℃) at the time of infection in the survival group were lower than those in the death group (P<0.05). Multivariate analysis showed that XDR-AB pulmonary infection was closely related to cardiac insufficiency, combined use of antifungal drugs and invasive ventilation of patients (P<0.05), all of which were risk factors for XDR-AB infection (P<0.05). The use of antibacterial drugs for less than 6 days was a protective factor (P<0.05). The likelihood ratio (χ², Wald χ²) test indicated that the model constructed was effective. The test of Hosmer-Lemeshow goodness of fit indicated a good fitting effect of the model. Conclusion: There are many influencing factors of disease outcome in patients with XDR-AB pulmonary infection. Patients with cardiac insufficiency, combined use of antifungal drugs and invasive mechanical ventilation are independent risk factors for XDR-AB infection, while the use of antibacterial drugs for less than 6 days is a protective factor. The Logistic regression prediction model has good predictive value for disease outcome in patients with XDR-AB pulmonary infection.