While a bicycle helmet protects the wearer's head in the event of a crash, not every user benefits to the same extent when wearing the headgear. A proper fit with the cyclist's head is found to be one of the most important attributes to improve protection during impact. A correct fit is defined as a small and uniform distance between the helmet liner and the wearer's head shape, with a broad coverage of the head area. The scientific community has recognised the need for improved fitting, but in-depth methods to analyse and compare the fit performance of distinct helmets models are still absent from the literature. We present a method based on 3D anthropometry, reverse engineering techniques and computational analysis to redress this shortcoming. As a result of this study, we introduce the Helmet Fit Index (HFI) as a tool for fit analysis between a helmet model and a human head. It is envisaged that the HFI can provide detailed understanding of helmet efficiency regarding fit and should be used during helmet development phases and testing.