PURPOSE: To present a validated model that reliably predicts unplanned readmission after upper extremity/hand surgery. METHODS: A total of 83,409 hand surgery patients were identified using the 2012-2019 ACS-NSQIP databases. Thirty-day unplanned readmission was defined as unexpected readmission for a postoperative occurrence related to the principal hand surgery. Independent predictors of 30-day unplanned readmission were identified using multivariable logistic regression with backward variable selection on the testing sample. Subsequently, the predictors were weighted according to β-coefficients to generate an integer-based New Risk Score (NRS) predictive of readmission. The NRS was then tested on the original sample and validated on NSQIP patients who had undergone hand surgery in 2020 (n = 15,247). The NRS was compared to two other widely used risk scores with receiver operating characteristics (ROC) analysis. RESULTS: The rate of 30-day unplanned readmission in the 2020 cohort was 1.1%. Independent risk factors included female gender, emergent case, diabetes, dyspnea, underweight BMI, ASA Class 5, smoking, hypertension, dialysis dependence, wound infection, chronic steroid use, weight loss, transfusion prior to surgery, and SIRS/sepsis (all P < 0.05). ROC analysis of the validation (2020) cohort rendered an area under the curve of 0.754, which demonstrates the accuracy of this prediction model. The mFI-5 and mCCI rendered AUCs of 0.686 and 0.704, respectively. CONCLUSION: We present a validated risk stratification tool for unplanned readmissions following hand surgery. Future studies should determine if implementation of this NRS optimizes safety and reduces readmission rates in hand surgery patients.