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Introduction: Acute postoperative pain affects time to opioid cessation and quality of life, and is associated with chronic pain. Effective screening tools are needed to identify patients at increased risk of experiencing more severe acute postoperative pain, and who may benefit from multimodal analgesia and early pain management referral. In this study, we develop a nomogram to preoperatively identify patients at high risk of moderate-severe pain following mastectomy., Methods: Demographic, psychosocial, and clinical variables were retrospectively assessed in 1195 consecutive patients who underwent mastectomy from January 2019 to December 2020 and had pain scores available from a post-discharge questionnaire. We examined pain severity on postoperative days 1-5, with moderate-severe pain as the outcome of interest. Multivariable logistic regression was performed to identify variables associated with moderate-severe pain in a training cohort of 956 patients. The final model was determined using the Akaike information criterion. A nomogram was constructed using this model, which also included a priori selected clinically relevant variables. Internal validation was performed in the remaining cohort of 239 patients., Results: In the training cohort, 297 patients reported no-mild pain and 659 reported moderate-severe pain. High body mass index (p = 0.042), preoperative Distress Thermometer score ≥4 (p = 0.012), and bilateral surgery (p = 0.003) predicted moderate-severe pain. The resulting nomogram accurately predicted moderate-severe pain in the validation cohort (AUC =  0.735)., Conclusions: This nomogram incorporates eight preoperative variables to provide a risk estimate of acute moderate-severe pain following mastectomy. Preoperative risk stratification can identify patients who may benefit from individually tailored perioperative pain management strategies and early postoperative interventions to treat pain and assist with opioid tapering., (© 2022. Society of Surgical Oncology.)