Abstract-Goal: In this work, we used in silico patientspecific models constructed from 3D delayed-enhanced magnetic resonance imaging (DE-MRI) to simulate intracardiac electrograms (EGM). These included electrically abnormal electrograms as these are potential radiofrequency ablation (RFA) targets. Methods: We generated signals with distinguishable macroscopic normal and abnormal characteristics by constructing MRIbased patient-specific structural heart models and by solving the simplified biophysical Mitchell-Schaeffer model of cardiac electrophysiology. Then, we simulated intracardiac electrograms by modelling a recording catheter using a dipole approach. Results: Qualitative results show that simulated EGM resemble clinical signals. Additionally, the quantitative assessment of signal features extracted from the simulated EGM showed statistically significant differences (p<0.0001) between the distributions of normal and abnormal electrograms, similarly to what is observed on clinical data. Conclusion: We demonstrate the feasibility of coupling simplified cardiac EP models with imaging data to generate intracardiac EMG. Significance: These results are a step forward in the direction of the pre-operative and non-invasive identification of ablation targets to guide RFA therapy.Index Terms-cardiac electrophysiology modelling, intracardiac electrogram modelling, radiofrequency ablation planning, electroanatomical mapping.