Abstract Background Computational models are pivotal for understanding electrophysiological aspects of cardiac diseases. Despite pigs' increased use in research, limited in vitro porcine data impedes accurate mathematical modeling. In this context, we recently developed a novel knock-in porcine model of long QT syndrome type 8 (LQT8) [1]. Purpose To develop a novel computational model for electrophysiology and Ca2+ handing in wild-type and LQT8 swine ventricular cardiomyocytes. Methods We designed a mathematical model of wild-type swine action potential (AP) based on a wide range of cellular electrophysiological data. Using the ORd model [2] as a foundation, we re-parametrized main ionic currents using the Nelder-Mead algorithm. We then modified the model to simulate LQT8, evaluating its utility in exploring arrhythmogenic mechanisms and pharmacological approaches. For the L-type Ca Channel (LTCC), we replaced the original HH formulation with a Markov model based on [3], which was subsequently modified to account for a population of mutant p.G406R channels. Selected biomarkers for validation were AP duration at 20, 50, and 90% of repolarization, maximum upstroke velocity, AP amplitude and resting membrane potential. To assess the robustness of the model, we generated a random population of 500 models accounting for biological variability by sampling key parameters in the range [-20 to +20%] of their original values, using the Latin Hypercube Sampling. Simulations were executed using MATLAB R2023a. Numerical integration was performed utilizing the MATLAB function ode15s. Results The mathematical model accurately reproduced a wide range of experimental data, including steady-state curves of the main ionic currents, kinetic properties of LTCC, APD rate dependency, maximum upstroke velocity and Ca2+transient morphology. The model successfully simulated AP prolongation in LQT8. Also, it replicated key features of the cellular phenotype such as steeper APD rate adaptation, increased duration and amplitude of the Ca2+ transients, increased CaMKII-mediated late Na+ current, pathologically decreased upstroke velocity with increasing pacing frequency, due to a CaMKII-mediated mechanism. As a proof-of-concept, the model was utilized to investigate arrhythmogenic mechanisms and pharmacological approaches for LQT8. According to model’s prediction, early afterdepolarizations (EADs) in LQT8 can stem from three distinct mechanisms: improper kinetics of late Na+ current, improper kinetics of LTCC, and enhanced late-systolic SR Ca release. Notably, the model also predicts that full CaMKII inhibition effectively eliminates EADs for all three mechanisms, showcasing the potential efficacy of this pharmacological intervention. Conclusions A novel mathematical swine ventricular myocyte model explores arrhythmogenic mechanisms and therapeutic interventions, aiding LQT8 research and clinical translation in cardiac disorders.