Conductive Polymer Composite (CPC) can be considered one of the best material candidates for the bipolar plates in Polymer Electrolyte Membrane (PEM) fuel cells due to its balance between electrical and mechanical properties, low cost and ease of manufacturing. The development of the models has been shown to be important for predicting the electrical properties of the CPCs. The main challenge is to produce a constant electric supply in the fuel cell systems which influence the overall fuel cell performance. Generally, the classical percolation theory describes that the electrical conductivity of the polymer composite is achieved when the volume fraction of the conductive filler is above the specific value, known as percolation threshold phenomena. Current research trends using the General Effective Media (GEM) model show it is the best model to predict the electrical properties of the composite. The main advantage of using the GEM is the model can predict the electrical conductivity for multiple filler systems at high filler loadings. Numerous factors including volume fraction, shape and size, aspect ratio, critical value, and orientation are significant in developing a robust model. Controlling the filler orientations in the CPCs are important as they are able to improve the mechanical performance while enhancing the electrical conductivity of the composite. Orientation can be induced by a few methods such as shear stress, altering die and fillers aspect ratio based on the needs. By controlling the fillers direction, one is able to control both the mechanical and electrical conductivity of the CPCs. However, recent publications seem to suggest that the Fibre Contact Model (FCM) is the latest model that considers the orientation factor in predicting conductivity. A good agreement between experimental results and modelling prediction can be observed using carbon-fibre reinforced polypropylene below and above the percolation threshold. Parallel orientations of the fibres to the extrusion die direction provided better electrical conductivity compared to randomly oriented fillers. This manuscript attempts to discuss other potential models used in predicting the electrical conductivity of the CPCs. (C) 2016 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.