Objective To explore the influencing factors of preoperative anxiety and depression status in patients undergoing laparoscopic myomectomy, and to analyze their predictive value for postoperative pain. Methods A retrospective selection was made of 138 patients who underwent laparoscopic myomectomy at Shangqiu First People’s Hospital from January 2024 to September 2025 as the study subjects. Before the operation, the hospital anxiety and depression scale (HADS) was used to assess the anxiety and depression status of the patients, and the patients were divided into the anxiety and depression group and the control group according to the score levels. All patients received standardized patient-controlled intravenous analgesia (PCIA) after the operation, with the analgesic target being a resting VAS score of≤3 points. The clinical data of the patients were collected, and a multivariate Logistic regression model was used to analyze the independent risk factors of preoperative anxiety and depression, and a risk prediction model for poor postoperative analgesic effect (VAS≥4 points) was constructed. Results Age≤35 years old, educational level of high school or below, monthly family income＜5 000 yuan, and multiple fibroids were independent risk factors for preoperative anxiety and depression in patients undergoing laparoscopic myomectomy (all P＜0.05). Preoperative anxiety and depression, Operation time≥90 minutes, intraoperative blood loss≥100 ml were independent risk factors for poor postoperative analgesic effect (VAS≥4 points) (all P＜0.05); For the constructed risk prediction model, the area under the curve (AUC) of the receiver operating characteristic (ROC) curve was 0.586 (95%CI: 0.492-0.680). Conclusion The incidence of preoperative anxiety and depression in patients undergoing laparoscopic myomectomy was relatively high. Under the condition of conventional postoperative analgesia, the preoperative anxiety and depression status still significantly increases the risk of poor postoperative analgesic effect (VAS≥4 points), suggesting that it is an effective indicator for predicting increased analgesic demand and complexity of pain management.