Abstract: Objective To investigate the risk factors for the mortality of Intensive Care Unit （ICU） patients with Pseudomonas aeruginosa bloodstream infections, and to construct a predictive nomogram model to assist clinical decision-making. Methods Clinical data from 74 patients with Pseudomonas aeruginosa bloodstream infections in ICU of the First Affiliated Hospital of Sun Yat-sen University were gathered from January 2014 to December 2023. The patients were classified into the survival group（n = 52） and mortality group （n = 22） based on the prognosis. Univariate and multivariate Cox regression analyses were used to screen for independent prognostic factors, and a predictive nomogram model was constructed. The predictive performance and accuracy of the model were verified. Results Acute physiology and chronic health status scoreⅡ （APACHEⅡ） >20 and multiple organ dysfunction syndrome （MODS） were the independent risk factors for the mortality of ICU patients with Pseudomonas aeruginosa bloodstream infections （both P < 0.05）. The nomogram model was constructed based on these two independent risk factors, with a concordance index （C-index） of 0.759. The predictive efficiencies for survival probabilities at 7 days and 14 days were 0.776 and 0.844. Calibration curve and clinical decision curve showed that the model had good predictive efficiency. Conclusions A time-dynamic predictive nomogram model is constructed for the risk factors of the mortality of ICU patients with Pseudomonas aeruginosa bloodstream infections, which could effectively predict the risk of mortality of such patients. This model can assist clinicians to rapidly identify high-risk patients and optimize antibiotic use strategies.