In this work, a voxel-based methodology is introduced for the hybridization of a pore network with interspersed nano-porous material elements allowing pore network based oxygen diffusivity calculations in a 3D image of a polymer electrolyte membrane (PEM) fuel cell gas diffusion layer (GDL) with an embedded microporous layer (MPL). The composite GDL is modeled by combining a hybrid network of block MPL elements with prescribed bulk material properties and a topologically equivalent network of larger discrete pores and throats that are directly derived from the 3D image of the GDL substrate. This hybrid network was incorporated into a pore network model, and effective diffusivity predictions of GDL materials with MPL coatings were obtained. Stochastically generated numerical models of carbon paper substrates with and without MPLs were used, and the pore space was directly extracted from this realistic geometry as the input for the pore network model. The effective diffusion coefficient of MPL-coated GDL materials was predicted from 3D images in a pore network modeling environment without resolving the nano-scale structure of the MPL. This method is particularly useful due to the disparate length scales that are involved when attempting to capture pore-scale transport in the GDL. Validation was performed by comparing our predicted diffusivity values to analytical predictions, and excellent agreement was observed. Upon conducting a mesh sensitivity study, it was determined that an MPL element size of 7 mm provided sufficiently high resolution for accurately describing the MPL nano-structure. (C) 2016 Elsevier Ltd. All rights reserved.