The goal of this study was to establish a risk stratification nomogram to aid in determining the need for inpatient admission among patients who were eligible for Medicare and were undergoing primary total shoulder arthroplasty (TSA). The American College of Surgeons National Surgical Quality Improvement Program database was queried to identify all patients older than 65 years who underwent primary TSA between 2006 and 2016. The primary outcome measure was inpatient admission, as defined by hospital length of stay longer than 2 days. Multiple demographic, comorbid, and peri-operative variables were used in a multivariate logistic regression model to yield a risk stratification nomogram. A total of 1514 inpatient and 6020 out-patient admissions were analyzed. Age older than 80 years (odds ratio [OR], 2.69; P<.0001; 95% CI, 2.21-3.27), female sex (OR, 2.18; P<.0001; 95% CI, 1.90-2.51), dependent functional status (OR, 1.69; P<.0001; 95% CI, 1.2-2.38), dialysis (OR, 3.48; P=.029; 95% CI, 1.14-10.63), admission from an inpatient facility (OR, 1.76; P<.0001; 95% CI, 1.70-1.82), and inflammatory arthritis (OR, 1.69; P<.02; 95% CI, 1.25-13.78) were the greatest determinants of inpatient stay. The resulting predictive model showed acceptable discrimination and calibration. Our model enabled reliable and straightforward identification of the most suitable candidates for inpatient admission among patients who were eligible for Medicare and were undergoing primary TSA. Patients who were receiving dialysis, who had dyspnea at rest, and who had bleeding disorders were more likely to be admitted as inpatients after TSA. Larger multicenter studies are necessary to externally validate the proposed predictive nomogram. [Orthopedics. 2022;45(1):43-49.].