Purpose: This study was done to provide fundamental data for developing a depression prediction model by discovering main factors that affect depression in patients who do maintenance hemodialysis. Method: The subjects were 191 patients doing maintenance hemodialysis selected from outpatient dialysis clinics at 9 major general hospitals, The Instrument tools utilized in this study were adapted from depression, fatigue, sleep disturbance, stress, adaptation, symptoms, daily activities, and role limitation and thoroughly modified to verify reliability and validity. The collected data was analyzed with a SPSS-PC 11.0 Window Statistics Program for real numbers, percentage, average, standard deviation, and multiple regression. Results: The correlation factor for depression was (M=2.54) fatigue(M=3.12), sleep disturbance (M=2.82), stress(M=3.04), adaptation(M=2.53), daily activities(M=2.24), symptoms(M=2.37), and role limitation(M=2.24). The strongest factor that affected depression was explained by symptoms of the patients who performed hemodialysis. The analysis of the factors that affected depression revealed a $58.4\%$ prediction in symptoms, stress, role limitation, and adaptation. Conclusion: It has been confirmed that the regression equation model(Depression=7.351 + .266$^{ast}$symptoms + .260$^{ast}$stress -.l89$^{ast}$adaptation + .057$^{ast}$fatigue) of this research may serve as a prediction factor for depression in Hemodialysis Patients.