Patients diagnosed with non-ischemic dilated cardiomyopathy (DCM) are at high risk of sudden cardiac death (SCD) and ventricular arrhythmias. Therefore, early identification is vital to guide preventive measures. In this study, a pipeline was developed to generate virtual cardiac patient-specific models with dilated cardiomyopathy, also known as digital twins. Electrocardiogram (ECG) and cardiac magnetic resonance (MRI) were used as input data for the pipeline. Based on the MRI we were able to create the geometrical models of the patients, including important features such as the fibrotic region, border zone, and fiber orientation. Subsequently, the ECG was used to calibrate important parameters of the model. The models presented in this study can be used in future work to assist in the clinical practice of cardiology and improve the understanding of the mechanisms underlying the generation of arrhythmias. The investigation of how digital twins can be used for arrhythmic risk stratification in patients with non-ischemic dilated cardiomyopathy is a relevant topic.