Multiaxial Warp Knitted (MWK) Fabrics are used to create Carbon Fibre Reinforced Plastic (CFRP) laminates. In contrast to Prepregs, CFRP laminates made with MWK fabrics are of interest because they could lower costs and processing time by being already constructed with multiple layers and through the use of a hot air oven instead of an autoclave. Defect in the form of fibre angle orientation plays an important role in the compression strength for laminates made with MWK fabrics. The in-plane and out-of-plane waviness of the fibres were characterised by the standard deviation of the angular waviness: sample Standard deviation of Fibre In-plane (SFI) and the sample Standard deviation of Fibre Out-of-plane (SFO). The SFI value was found in two ways: analysis (Multiple Field Image Analysis (MFIA) technique) software and Fibre Image Analysis software. Measurements of the holes in the carbon fibre textile, colloquially known as “fisheyes,” caused by sewing the textile together were also gathered. The SFI, SFO, and “fisheye” dimensions were together used in the FMB-PMB model and the Unit Cell Model to calculate the compression strength. These predicted compression strengths were compared to the laboratory results. Also, a reliability model was developed to find R, the reliability of each textile, to be used as a textile classification tool. It has been found that the compression strength predictions found using analysis and Fibre Image Analysis yielded similar results, with predictions from analysis closer to the laboratory results. The R value yielded a positive correlation with the results from analysis. A large percentage of difference between the predicted and the actual compression strength was observed for some textiles. This could be attributed to the inherent lack of regularity for some of the examined textiles and variability in determining the SFI and “fisheye” parameters. Improvements would involve devising rules and methods to determine the SFI and “fisheye” parameters, modifying the FMB-PMB and Unit Cell Models, and making the analysis process faster and more applicable for on-line quality process control.