Background and objectives <p>The monocyte count-to-albumin ratio (MAR) is a novel biomarker whose prognostic impact on critically ill patients with sepsis has not been extensively studied. The objective of this study is to investigate the predictive value of the MAR for prognosis in patients with sepsis.</p> Methods <p>A retrospective analysis was conducted using patient data from the MIMIC-IV database that met the criteria for sepsis diagnosis as the training set. A Cox regression analysis was performed to examine the relationship between MAR and the risk of mortality within 30&#xa0;days. Divide MAR into four quartiles (Q1, Q2, Q3, Q4) and conduct Kaplan–Meier survival analysis to compare the 30-day cumulative survival rates across the four patient groups. Then, perform a Cox regression analysis, using Q1 as the baseline reference. The Restricted Cubic Spline (RCS) method was used to analyze the non-linear relationship between MAR and mortality risk. The median MAR across all patients was used as the reference point to define the non-linear effect. Subsequent subgroup analyses were conducted to evaluate the reliability of MAR in predicting 30-day outcomes. Lasso regression analysis was used to select variables associated with 30-day mortality. These variables were then subjected to logistic regression to identify the key ones, which were used to construct a nomogram model. We evaluated the predictive efficacy of the nomogram for 30-day mortality in patients with sepsis using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curves (DCA). We adopted the reporting guidelines for prognostic studies. In addition, patients meeting the Sepsis-3 diagnostic criteria from the Intensive Care Unit (ICU) of the Xinjiang Uygur Autonomous Region People's Hospital were collected as clinical validation set data. Due to missing Sapsii scores for patients in our hospital's case database, we were unable to collect the data. These clinical data were then applied to the predictive model to validate its predictive performance.</p> Results <p>This study enrolled 2188 patients with sepsis from the MIMIC-IV database and 224 patients with sepsis from the People's Hospital of Xinjiang Uygur Autonomous Region. The 2188 patients constituted the training cohort, which included 1088 (49.7%) fatal cases. Cox regression analysis revealed a positive association between the monocyte-to-albumin ratio (MAR) and the risk of 30-day mortality, with a hazard ratio of 1.038 (95% confidence interval 1.028–1.047). Kaplan–Meier curves demonstrated that patients with higher MAR values had a significantly lower cumulative 30-day survival rate. Subsequent Cox regression, using the first quartile (Q1) as the reference, indicated that higher MAR quartiles were associated with an increased mortality risk. Subgroup analysis further confirmed the robustness of these findings. A nomogram incorporating MAR and other factors outperformed the Sofa and Sapsii scores in predicting 30-day sepsis mortality, demonstrating superior discrimination and calibration. Using the 224 patients from Xinjiang as a validation cohort, ROC curve analysis yielded AUC values of 0.764 for the training set and 0.772 for the validation set. DeLong's test showed no statistically significant difference between the two AUCs. The calibration curves for both cohorts closely aligned with the ideal line, indicating good agreement between predicted and observed outcomes. Decision curve analysis provided evidence for the model's high clinical utility and significant net benefit.</p> Conclusions <p>Elevated MAR levels constitute an independent risk factor for increased 30-day mortality in patients with sepsis. This measure effectively predicts 30-day mortality in this population. A nomogram incorporating MAR, age, lactate, mechanical ventilation, vasoactive drug use, and hemoglobin demonstrated excellent predictive performance. External validation with clinical datasets confirmed the model's robust predictive capability and its significant value for clinical decision support.</p>