Thrombotic thrombocytopenic purpura (TTP) is a life-threatening disease, and its mortality rate is 10% to 20%. However, there are currently only a few markers to predict the prognosis in patients with TTP. We aimed to identify several clinical indices and laboratory parameters for predicting the prognosis of TTP at admission.A single-centre observational cohort study that included patients with TTP from the First Affiliated Hospital of Zhengzhou University in China was conducted from January 1, 2012 to November 30, 2018. The primary outcome was prognosis, including in-hospital mortality, major thromboembolic events, or failure to achieve remission at discharge. We used the random forest method to identify the best set of predictors.Eighty-seven patients with TTP were identified, of whom 12 died during the treatment. The total number of patients within-hospital mortality, major thromboembolic events, and failure to achieve remission at discharge was 58. The machine learning method showed that the D-dimer level was the strongest predictor of the primary outcome. Receiver operating characteristic (ROC) analysis demonstrated that the sensitivity and specificity of the D-dimer level alone for identifying high-risk patients were 78% and 81%, respectively, with an optimum diagnostic cut-off value of 770 ng/mL. The area under the ROC curve (AUC) was 0.80, and the 95% confidence interval (CI) was 0.70 to 0.90.This study found that the D-dimer level exhibited a good predictive ability for prognosis in patients with TTP. These findings may aid in the development of new and intensive treatment strategies to achieve remission among high-risk patients. However, external validation is necessary to confirm the generalizability of our approach across populations and treatment practices.