Purpose: The purpose of this study was to identify predictors of emergency room visit in patients with hemodialysis. Methods: The subjects of the study were 195 hemodialysis patients in K University D Hospital in Daegu. The measurement tools were social support, BDI (Beck Depression Inventory), knowledge about hemodialysis, self-efficacy, and self-management behavior. Dialysis-related characteristics and physiological indicators were retrieved from the electronic medical record. The data were analyzed using t-test, chi-square test, and logistic regression analysis. Results: Among 195 hemodialysis patients, 42.1% had visited emergency room, and 57.9% didn’t visit emergency room. In the emergency room visit group, candidate predictor variables were diabetes (p=.002), hospitalization experience after hemodialysis (p<.001), number of medication (p<.001), complication status (p=.021), heart disease (p= .047), level of erythropoietin stimulation agents (p=.006), systolic blood pressure (p=015), hemoglobin (p=.005), WBC (p=.017), glucose (p=.003) and depression (p<.001). Among the 11 variables entered into the logistic regression model, moderate depression (CI=1.51-10.50, OR=3.98), severe depression (CI=1.85-10.54, OR=4.42), history of hospitalization after initiation of hemodialysis 1–2 times (CI=1.42-9.25, OR=3.63), and ≥3 times (CI=1.55-10.37, OR=4.01), presence of diabetes mellitus (CI=1.04-5.57, OR=2.41), higher erythropoiesis-stimulating agent (ESA) dose (CI=1.07-5.23, OR=2.37), and greater number of prescribed medications (CI=1.11-5.75, OR=2.53) were identified as significant predictors. The overall predictive accuracy of the model was 75.4%. Conclusion: In order to reduce emergency department visit among hemodialysis patients, it is essential for both patients and healthcare professionals to focus on the identified predictors. Furthermore, the development of nursing interventions targeting these predictors and evaluation of their effectiveness are warranted.