Ventricular arrhythmias are the leading cause of mortality in patients with ischemic heart diseases, such as myocardial infarction (MI). Computational simulation of cardiac electrophysiology provides insights into these arrhythmias and their treatment. However, only sparse information is available on crucial model parameters, for instance, the anisotropic intracellular electrical conductivities. Here, we introduced an approach to estimate these conductivities in normal and MI hearts. We processed and analyzed images from confocal microscopy of left ventricular tissue of a rabbit MI model to generate 3D reconstructions. We derived tissue features including the volume fraction of myocytesVmyo, gap junctions-containing voxelsVgj, and fibrosisVfibrosis. We generated models of the intracellular space and intercellular coupling. Applying numerical methods for solving Poisson’s equation for stationary electrical currents, we calculated normalσmyo,n, longitudinalσmyo,l, and transverseσmyo,tintracellular conductivities. Using linear regression analysis, we assessed relationships of conductivities to tissue features.VgjandVmyowere reduced in MI vs. control, butVfibrosiswas increased. Bothσmyo,landσmyo,nwere lower in MI than in control. Differences ofσmyo,tbetween control and MI were not significant. We found strong positive relationships ofσmyo,lwithVmyoandVgj, and a strong negative relationship withVfibrosis. The relationships ofσmyo,nwith these tissue features were similar but less pronounced. Our study provides quantitative insights into the intracellular conductivities in the normal and MI heart. We suggest that our study establishes a framework for the estimation of intracellular electrical conductivities of myocardium with various pathologies.