Ischemia, diffuse fibrosis, and long QT syndrome are well-known triggers and substrates for cardiac arrhythmia. In this paper, we use computational modeling of cardiac electrophysiology—a cutting-edge technique that allows for detailed examination of individual mechanisms while also providing a platform to explore their synergistic effects—to investigate how these conditions, both individually and in combination, contribute to the development of cardiac arrhythmias. Our computational modeling approach includes sub-cellular and tissue-level adjustments to reflect alterations in the genesis and propagation of action potentials (APs). To assess the pro-arrhythmic potential of these conditions, we employed numerical simulations and used the vulnerability (or vulnerable) window metric, defined as the time interval in which a premature extrasystole can induce arrhythmias, combined with a virtual electrocardiogram (ECG) reading, to better describe the condition being studied. Our results match each condition’s individual impact to the tissue, which we inspected by various intervals of vulnerability window (VW) and thus different amounts of cardiac arrhythmias. This work underscores the importance of computational modeling in cardiology, as it allows us to explore complex interactions in a controlled environment, providing insights that might be challenging to obtain through traditional methods. By leveraging computational techniques, we can better understand the mechanisms underlying cardiac arrhythmia and develop more effective therapeutic strategies.