Nanobodies (Nbs) have emerged as a promising class of biologics. Despite having marked physicochemical properties, Nbs are derived from camelids and may require humanization to improve translational potentials. By systematically analyzing the sequence and structural properties of Nbs, we found substantial framework diversities and revealed the key differences between Nbs and human immunoglobulin G antibodies. We identified conserved residues that may contribute to enhanced solubility, structural stability, and antigen binding, providing insights into Nb humanization. Based on big data analysis, we developed "Llamanade," an opensource software to facilitate rational humanization of Nbs. Using sequence as input, Llamanade can rapidly extract sequence features, model structures, and optimize solutions to humanize Nbs. Finally, we used Llamanade to successfully humanize a cohort of structurally diverse and potent SARS-CoV-2 neutralizing Nbs. Llamanade is freely available and will be easily accessible on a server to support the development of therapeutic Nbs into safe and effective trials.