Introduction: Non-ischemic cardiomyopathy (NICM) encompasses a heterogeneous group of myocardial diseases ranging from genetic to inflammatory etiologies, that are not related to coronary artery disease. Despite therapeutic advances, NICM is associated with dangerous arrhythmias such as ventricular tachycardia (VT) and sudden cardiac death. Although catheter ablation is widely used to control VT, current clinical imaging often fails to accurately localize patient-specific arrhythmogenic regions. This work proposes a patient-specific computational modeling pipeline to characterize the electrophysiological substrate of a subject affected by NICM secondary to acute myocarditis. Methods: The patient-specific geometry of the left ventricle (LV) reconstructed from late gadolinium-enhanced magnetic resonance images (LGE-MRI) was discretized with a high-resolution hexahedral mesh, together with myocardial fiber orientation and transmural heterogeneity definition. In addition, the scar identified in the LGE-MRI data set was mapped onto the ventricular mesh. The pathological modifications to the healthy LV have been analyzed with three distinct modeling approaches: i) a purely structural model considering only a localized conductivity reduction; ii) a purely cellular model incorporating myocyte-fibroblast electrotonic coupling; and iii) a full model integrating both modifications. Electrophysiological simulations were performed using the Ten Tusscher-Panfilov model for human ventricular myocytes. Results: The results prove that the full model successfully replicates the electrophysiological alterations observed in clinic, while the structural and cellular modifications alone only capture partial aspects of the pathology. Moreover, the model exhibits a total activation time consistent with clinical expectations and reproduces an anatomically defined slow-conducting channel compatible with a re-entrant pathway. The identification of this isthmus provides a suitable substrate for subsequent VT induction simulations. Ultimately, the developed pipeline serves as a foundational step forward for the development of in-silico clinical tools, which offer a non-invasive platform for the identification of critical arrhythmogenic targets and supporting personalized ablation strategies to improve patient outcomes.