〔Abstract〕 Objective To explore the risk factors of fever after hysterectomy in patients with uterine fibroids, and establish a nomogram prediction model to provide theoretical guidance for clinical diagnosis and treatment. Methods The data of patients who underwent hysterectomy due to uterine fibroids were collected and randomly divided into training group and validation group at 6 ∶4. Univariate and multivariate analyses were performed by χ2test and Logistic regression model analysis. The nomogram was established based on the results of multivariate analysis, the calibration curve and receiver operating characteristic, curve were used to evaluate the prediction ability and accuracy of the nomogram. The decision curve reflected the clinical application value of the model. Results Among 264 patients in the training group, 33 patients had fever, and the postoperative disease rate was 12.5%. The results of univariate and multivariate analysis showed that anemia, preoperative curettage, operation scope and operation time were independent risk factors for fever after hysterectomy in patients with uterine fibroids. The internal and external calibration curves had a good fit with the actual observation results, with an average error of 0.031 and 0.025, respectively. The area under receiver operating characteristic curve of the internal and external verification of the nomogramare 0.788 and 0.712, respectively, reflecting the good predictive ability of the model. The decision curve showed that the model had good clinical benefit in a certain threshold range. Conclusion Based on multivariate analysis, the independent risk factors of fever after hysterectomy in patients with uterine fibroids, including anemia, preoperative curettage, operation scope and operation time. In addition, we established a nomogram with good predictive ability and accuracy, which is helpful for clinicians to timely manage fever after hysterectomy in patients with uterine fibroids and guide clinical individualized treatment.