This study developed an XGBoost machine learning model using intraoperative blood pressure time-series data to predict the risk of acute kidney injury (AKI) after Type A acute aortic dissection repair. The model, which outperformed others in accuracy, identified factors like intraoperative urine output and the duration of mean arterial pressure below 65 mmHg as critical predictors for postoperative AKI.