Brown dwarfs are a unique class of object which span the range between the lowest mass stars, and highest mass planets. New insights into the physics and chemistry of brown dwarfs comes from the comparison between spectroscopic observations, and theoretical atmospheric models. In this thesis, I present a uniform atmospheric retrieval analysis of the coolest Y, and late-T spectral type brown dwarfs using the CaltecH Inverse ModEling and Retrieval Algorithms (CHIMERA). In doing so, I develop a foundational dataset of retrieved atmospheric parameters including: molecular abundances, thermal structures, evolutionary parameters, and cloud properties for 61 different brown dwarfs. Comparisons to other modeling techniques and theoretical expectations from the James Webb Space Telescope (JWST) are made. Finally, I describe the techniques used to improve CHIMERA to run on Graphical Processing Units (GPUs), which directly enabled the creation of this large dataset.