This study presents an interactive open resource for benchmarking brain morphology derived from MRI data across the human lifespan. The researchers compiled 123,984 MRI scans from 101,457 participants, spanning from 115 days post-conception to 100 years of age, to create brain charts that quantify age-related changes in brain structure. These charts use centile scores based on non-linear trajectories of brain structural changes and rates of change, enabling the identification of previously unreported neurodevelopmental milestones and demonstrating robustness to technical and methodological differences between studies. Centile scores showed increased heritability compared to non-centiled MRI phenotypes and provided a standardized measure of atypical brain structure, revealing patterns of neuroanatomical variation across neurological and psychiatric disorders. The study highlights the importance of normative brain charts for standardized quantification of brain structure over the lifespan, particularly for research on psychiatric disorders and neurodegenerative diseases. The researchers used generalized additive models for location, scale and shape (GAMLSS) to model non-linear growth trajectories, accounting for site- and study-specific batch effects. The brain charts identified key developmental milestones, such as the peak of grey matter volume at 5.9 years and white matter volume at 28.7 years, and showed that brain development is highly sensitive to scanner platforms, data quality, and processing methods. The study also found that centile scores of brain metrics were significantly associated with neuropsychiatric disorders and dimensional phenotypes, and that centile scores showed increased heritability compared to raw volumetric data. The brain charts were validated across multiple studies and showed high stability across longitudinal assessments. The researchers also demonstrated that centile scores could be used to benchmark individual scans against normative trajectories, enabling the detection of atypical brain structure and providing standardized effect sizes for neuroanatomical atypicality across clinical disorders. The study emphasizes the importance of normative brain charts for understanding brain development and aging, and for improving the diagnosis and treatment of neurological and psychiatric disorders. The researchers also highlight the need for increased ethnic, socioeconomic, and demographic diversity in MRI research to improve the accuracy and generalizability of normative trajectories. The study provides an open resource for the neuroimaging research community to accelerate progress in standardized quantitative assessment of MRI data.This study presents an interactive open resource for benchmarking brain morphology derived from MRI data across the human lifespan. The researchers compiled 123,984 MRI scans from 101,457 participants, spanning from 115 days post-conception to 100 years of age, to create brain charts that quantify age-related changes in brain structure. These charts use centile scores based on non-linear trajectories of brain structural changes and rates of change, enabling the identification of previously unreported neurodevelopmental milestones and demonstrating robustness to technical and methodological differences between studies. Centile scores showed increased heritability compared to non-centiled MRI phenotypes and provided a standardized measure of atypical brain structure, revealing patterns of neuroanatomical variation across neurological and psychiatric disorders. The study highlights the importance of normative brain charts for standardized quantification of brain structure over the lifespan, particularly for research on psychiatric disorders and neurodegenerative diseases. The researchers used generalized additive models for location, scale and shape (GAMLSS) to model non-linear growth trajectories, accounting for site- and study-specific batch effects. The brain charts identified key developmental milestones, such as the peak of grey matter volume at 5.9 years and white matter volume at 28.7 years, and showed that brain development is highly sensitive to scanner platforms, data quality, and processing methods. The study also found that centile scores of brain metrics were significantly associated with neuropsychiatric disorders and dimensional phenotypes, and that centile scores showed increased heritability compared to raw volumetric data. The brain charts were validated across multiple studies and showed high stability across longitudinal assessments. The researchers also demonstrated that centile scores could be used to benchmark individual scans against normative trajectories, enabling the detection of atypical brain structure and providing standardized effect sizes for neuroanatomical atypicality across clinical disorders. The study emphasizes the importance of normative brain charts for understanding brain development and aging, and for improving the diagnosis and treatment of neurological and psychiatric disorders. The researchers also highlight the need for increased ethnic, socioeconomic, and demographic diversity in MRI research to improve the accuracy and generalizability of normative trajectories. The study provides an open resource for the neuroimaging research community to accelerate progress in standardized quantitative assessment of MRI data.