Heart failure is a complex clinical syndrome in which the heart cannot pump enough blood to meet the body's demands. It is a significant health problem which affects 1-2% of adults worldwide. In this thesis, it was investigated whether a personalized computer model of the heart can be used to predict the effect of pacemaker therapy in patients with heart failure. Wall motion patterns of the heart, obtained using echocardiography, were integrated into the CircAdapt model of the human heart and circulation to create a digital twin of the patient. In this digital twin, which is a virtual representation of the real patient, a pacemaker therapy was simulated to predict the degree of cardiac pump function improvement within the model. It was found that predictions in the digital twin were indicative of the real clinical outcome which was observed in the patient. In the future, this digital twin technology could serve as a diagnostic and therapeutic support tool in patients with heart failure.

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