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A bstract Aims We aim to develop a patient-specific computational model to predict the risk of Ventricular Tachycardia (VT) in patients with Biventricular Cardiac Resynchronization Therapy (BiV-CRT) device. Patients are indeed at risk of developing arrhythmias due to BiV-CRT pacing, a known potential complication that puts the cardiologist on guard against its prevention. Materials and Methods We consider three non-ischemic fibrotic patients. Patient-specific left ventricle geometries and fibrosis regions are extracted from Cine-MRI and LGE-MRI. The electrophysiology model, based on the monodomain equation and on the Ten Tusscher-Panfilov (TTP06) ionic current model, is personalized using pre-operative Electro-Anatomical Mappings System data. The TTP06 parameters are adapted to reflect the altered electrical properties of the fibrotic tissue. To test inducibility, we use an 𝕊1−𝕊2 stimulation protocol: 𝕊1 simulates the clinical BiV-CRT pacing with patient-specific VV-delay, followed by a 𝕊2 ectopic impulse. This procedure is repeated for ten ectopic sites. The arrhytmogenic risk is quantified by the number of ectopic sites that successfully generates a reentry loop. Conclusion The model’s prediction of VT risk is consistent with the long-term clinical follow-up for all the patients. Arrhythmic patients show a higher number of ectopic sites from which a reentry loop is generated compared to the non-arrhythmic patient. This study provides a first, preliminary attempt towards the use of computational tools in assessing the vulnerability of the arrhythmic substrate during BiV-CRT pacing in non-ischemic patients. In future, such tools could serve as a powerful non-invasive diagnostic metric to inform clinicians about possible therapies to associate to BiV-CRT.