Background: Multiple longitudinal responses together with time-to-event outcome are common in biomedical studies. There are several instances where the longitudinal responses are correlated with each other and at the same time each longitudinal response is associated with the survival outcome. The primary goal of this study was to present and explore a bivariate joint modeling approach for the bivariate longitudinal change of blood pressures and time to death of heart failure patients at Felege Hiwot Referral Hospital. Methods: A retrospective study design was used to collect relevant data on heart failure patients from the medical charts of 245 cases. A joint bivariate linear mixed-effects model and Weibull model were used for longitudinal and survival data respectively, to identify factors that jointly affect blood pressure and time to death of heart failure patients. The longitudinal model and the survival model were linked by random intercept and random slope association parameters. Results: The DBP change was significantly associated with the death of heart failure patients ( ; 95% CI: -2.09022, -0.0645; p-value=0.042 and ; 95% CI: -0.1600, -0.0672; p value=0.000). The analysis also showed that patients with 40%< Ejection fraction<50 % ( ; 95% CI: -1.7865, -0.9676; p-value=0.000), Ejection fraction>=50 %( ; 95CI: -0.8995, - 0.5528; p-value=0.000), used spironolactone treatment and high PR were significantly lowering the death of heart failure patients. Patients with age 46-55, 56-65, 66 and above, dilated cardiomyopathy ( ; 95% CI: 0.7203, 1.1254; p-value=0.000), Anemia, diabetic mellitus, chronic kidney disease, pneumonia, lower sodium, high Creatinine, New York Heart Association class III and class IV were significantly increased the death of heart failure patients. Similarly age group 56-65, 66 and above, sodium, Creatinine, pneumonia, Digoxin, Spironolactone were significantly lowering the DBP of patients also patients with 40 %< Ejection fraction<50%, hypertensive heart disease and platelets were significantly increased the DBP of heart failure patients. Conclusion: from clinical perspective, patients who had older age, less Ejection fraction, dilated cardiomyopathy, Anemia, diabetic mellitus, chronic kidney disease, pneumonia,, low sodium, high creatinine, no take spironolactone treatment, New York Heart Association class III, New York Heart Association class IV and high Pulse rate to experiences the death of heart failure. From methodology perspective, a joint model approach provides wide range information about the change of bivariate longitudinal and time to death model to provide dynamics prediction and increasing precise knowledge of diseases. Key words: Heart failure, Systolic blood pressure, Diastolic blood pressure, longitudinal analysis, survival analysis, joint model, MCMC method