Computational modeling has contributed to the understanding of the normal cardiac electrophysiology and the mechanisms underlying arrhythmogenesis and arrhythmia maintenance. Our improved understanding of cardiac physiology and access to faster computational power have allowed us to integrate many layers of biological systems, gain further insight into the mechanism of cardiac pathology and moved from small scale molecular and cellular models to integrated three-dimensional models representing the anatomy, electrophysiology and hemodynamic parameters on an organ scale. The ultimate goal of cardiac modeling is to create personalized patient-specific models that would allow clinicians to better understand the disease pathology, aid diagnosis and plan treatment strategy on a case-by-case basis. Pioneers in the field have demonstrated that such approach have already impacted on the diagnosis and therapeutic treatment for ventricular arrhythmia and heart failure. This review demonstrates the feasibility to integrate computational modeling with clinical investigations in a clinical environment and to guide therapeutic treatment of cardiac arrhythmia and heart failure in real time for individual patients.