Generally, evaluating transport in composites as a function of composition relies on a variety of measurements, making them a time-consuming endeavor. These measurements are tedious considering that processing, additives, binders, and any microstructural changes will influence the effective transport through the composite and that transport needs to be reevaluated every time. Aside from experimental approaches, microstructure-based simulations can offer valuable guidance when developing microstructural design concepts. Considering the meso-and even atomistic scale, Heo et al. investigated the impact of microstructure on ionic conductivity in Li7La3Zr2O12 computationally, while Haruyama et al. calculated optimized structures and properties of interfaces between oxidic cathode active material (CAM) and β-Li3PS4 using density functional theory. Microstructural modelling of entire composite cathodes can further reveal percolation behavior of ion-and electron-conducting clusters, while effective electronic and ionic conductivities can be calculated using flux-based simulations on composite microstructure representations. Finsterbusch et al. constructed a virtual twin based on scanning electron microscopy micrographs and subsequently simulated discharge curves. Extending this approach, Chen et al. utilized an electrochemical-thermal coupled model to simulate heat evolution in addition to discharge characteristics of composite cathodes. Nevertheless, these approaches are often computationally expensive and a faster predictive approach is desirable to screen the transport of new systems.