Galaxy clusters, because of their massive size, act as powerful lenses for background objects. The Hubble Frontier Fields project was a multiyear international colloboration to examine six galaxy clusters acting as gravitational lenses with the aide of the Hubble Space Telescope. Lens modelling teams used shared data to reconstruct the cluster mass distributions using a variety of methods. We used our free-form method Grale to solve for the mass distribution of each cluster. The only inputs used were related to the observed images, and unlike most other methods, no information about visible light of the cluster galaxies was part of the input. The lensing models produced by each modelling team were used to study magnified high redshift galaxies, and construct their luminosity functions. These scientific advances prepare the community ahead of the James Webb Space Telescope launch. Upon reconstructing the cluster distributions, our goal was to see if light traces mass and investigate Grale uncertainties. We focused on the first two Hubble Frontier Fields clusters, Abell 2744 and MACS J0416. No significant offsets were found between brightest cluster member galaxies and local mass peaks for either cluster on scales of ≈ 10 − 15kpc. We calculated the correlation function between cluster core member galaxies and mass distribution for each cluster. Our results confirmed the standard biasing scenario of galaxy formation, meaning the clustering of galaxies is heavily influenced by the underlying dark matter distribution. We found light traces mass within HFF clusters, Abell 2744 and MACS J0416. We directly compared two Abell 2744 Grale reconstructions to gauge the robustness of calculated uncertainties, and confirmed that Grale uncertainties were robust to changes in input data and slight modifications in the Grale code parameters. Moreover, both maps produced relatively low Lens-plane RMS values, comparable to those of other methods. We explained our method for calculating Lens-plane RMS, while also providing multiple alter- native definitions, because of a lack of consensus on the subject in the published literature.