This article presents an extensive resource for benchmarking brain morphology across the human lifespan using neuroimaging data. The authors aggregated 123,984 MRI scans from over 100 primary studies, spanning from conception to 100 years of age, to create brain charts. These charts provide a standardized measure of brain structure and development, allowing for the identification of previously unreported milestones and the assessment of individual differences. The charts are based on non-linear trajectories of brain structural changes and rates of change over the lifespan, and they show high stability across longitudinal assessments. The centile scores derived from these charts are sensitive to genetic and early-life environmental effects and can be used to quantify atypical brain structure in various neurological and psychiatric disorders. The study highlights the importance of standardized norms for neuroimaging data and demonstrates the feasibility of generating comprehensive brain growth charts using large-scale, diverse datasets. The authors also discuss the limitations and future directions of this work, emphasizing the need for further research to validate the clinical utility of brain charts and to address biases in the current dataset.This article presents an extensive resource for benchmarking brain morphology across the human lifespan using neuroimaging data. The authors aggregated 123,984 MRI scans from over 100 primary studies, spanning from conception to 100 years of age, to create brain charts. These charts provide a standardized measure of brain structure and development, allowing for the identification of previously unreported milestones and the assessment of individual differences. The charts are based on non-linear trajectories of brain structural changes and rates of change over the lifespan, and they show high stability across longitudinal assessments. The centile scores derived from these charts are sensitive to genetic and early-life environmental effects and can be used to quantify atypical brain structure in various neurological and psychiatric disorders. The study highlights the importance of standardized norms for neuroimaging data and demonstrates the feasibility of generating comprehensive brain growth charts using large-scale, diverse datasets. The authors also discuss the limitations and future directions of this work, emphasizing the need for further research to validate the clinical utility of brain charts and to address biases in the current dataset.