Fibre-reinforced polymer (FRP) composites have become indispensable in aerospace engineering over the past two decades, driving the need for efficient and standardized testing protocols to certify their reliability. However, no standardized protocol currently exists for fatigue testing of FRPs, particularly due to fibre bridging—a phenomenon prominent in testing but rarely encountered in real-world applications. This study investigates existing fatigue data processing techniques, with a primary focus on a regression-based approach that could standardize fatigue data analysis. Current fatigue delamination characterization methods often rely on single-parameter empirical models, which struggle to capture the complex interaction between cyclic and monotonic load components, expressed as ∆√G and Gmax, respectively. This study demonstrates that the regression method’s zero-bridging technique effectively incorporates both parameters, offering a comprehensive view of delamination growth by isolating it from fibre bridging effects. This approach suggests a shift away from the traditional 2D analysis to a 3D framework, which considers both Gmax and ∆√G, enabling a more accurate depiction of delamination behaviour across various stress ratios. Notably, the results reveal that zero-bridging data align on a common plane under consistent stress ratios, shifting as stress ratios increase. Additionally, fibre orientation influences data clustering, with similar orientations exhibiting stronger convergence than dissimilar ones. Comparison of this regression-based method with the modified Paris law reveals significant discrepancies in its current implementation, suggesting alternative approaches to address these limitations. This study also highlights the impact of data size and selection on the model behaviour, stressing their importance in accurate model representation. This research validates the regression method as a promising candidate for standardizing fatigue data processing, improving the precision and reliability of post-test analysis for fibre-reinforced polymer composites.