The article introduces the Pangolin tool, a computational method designed to assign the most likely Pango lineage to SARS-CoV-2 genome sequences. The tool addresses the challenge of managing and interpreting the vast amount of genomic data generated during the pandemic. Pangolin uses a machine learning model, pangoLEARN, trained on designated sequences and lineage designations, to assign lineages to new sequences. The tool is available as a web application and command-line tool, facilitating access to actionable information for researchers. The authors describe the development, performance, and limitations of Pangolin, highlighting its robustness to missing data, ambiguous sequences, and novel recombinant genomes. They also discuss future directions, including the potential for adapting the tool to other viral outbreaks and the need for regular updates to the training data. The Pangolin tool has been instrumental in facilitating genomic epidemiology and public health decision-making during the pandemic.The article introduces the Pangolin tool, a computational method designed to assign the most likely Pango lineage to SARS-CoV-2 genome sequences. The tool addresses the challenge of managing and interpreting the vast amount of genomic data generated during the pandemic. Pangolin uses a machine learning model, pangoLEARN, trained on designated sequences and lineage designations, to assign lineages to new sequences. The tool is available as a web application and command-line tool, facilitating access to actionable information for researchers. The authors describe the development, performance, and limitations of Pangolin, highlighting its robustness to missing data, ambiguous sequences, and novel recombinant genomes. They also discuss future directions, including the potential for adapting the tool to other viral outbreaks and the need for regular updates to the training data. The Pangolin tool has been instrumental in facilitating genomic epidemiology and public health decision-making during the pandemic.