UCSF ChimeraX is a powerful tool for structure building and analysis, offering advanced features for atomic model building, refinement, and validation. The software integrates machine-learning structure predictions, likelihood-based fitting in maps, and per-residue scoring to identify modeling errors. It also provides tools for analyzing mutations, post-translational modifications, and ligand interactions. ChimeraX supports cryo-electron microscopy (cryo-EM) and other structural biology techniques, with a wide range of built-in and community-developed extensions. The software is freely available for non-commercial use and can be accessed through its website. ChimeraX includes tools for protein structure prediction, such as AlphaFold and ESMFold, which can generate initial models for cryo-EM structures. These models can be refined using local EM fitting, which aligns predicted domains with cryo-EM maps. The software also allows for the addition of small-molecule ligands and solvent molecules, and provides tools for model refinement and assessment. QScore and StrudelScore are used to evaluate model fit to cryo-EM maps, while local map resolution tools help identify regions of lower resolution. ChimeraX also supports the analysis of additional experimental data, such as crosslinking and electron tomography, through extensions like XMAS and ArtiaX. The software is capable of building and modifying atomic structures independently of experimental data, and can prepare them for computational pipelines involving molecular docking or dynamics simulations. The software is easily extendable using Python and provides a user-friendly interface for integrating various steps in model building. ChimeraX is available for macOS, Windows, and Linux, and offers comprehensive documentation, tutorials, and contributed extensions. The software is widely used by the cryo-EM community for its robust visualization and analysis capabilities, and its integration of new methods and tools helps reduce the time and effort required to create accurate models. The authors of this article have contributed to the development and refinement of ChimeraX, and the software is supported by various funding sources, including the National Institutes of Health and the Chan Zuckerberg Initiative.UCSF ChimeraX is a powerful tool for structure building and analysis, offering advanced features for atomic model building, refinement, and validation. The software integrates machine-learning structure predictions, likelihood-based fitting in maps, and per-residue scoring to identify modeling errors. It also provides tools for analyzing mutations, post-translational modifications, and ligand interactions. ChimeraX supports cryo-electron microscopy (cryo-EM) and other structural biology techniques, with a wide range of built-in and community-developed extensions. The software is freely available for non-commercial use and can be accessed through its website. ChimeraX includes tools for protein structure prediction, such as AlphaFold and ESMFold, which can generate initial models for cryo-EM structures. These models can be refined using local EM fitting, which aligns predicted domains with cryo-EM maps. The software also allows for the addition of small-molecule ligands and solvent molecules, and provides tools for model refinement and assessment. QScore and StrudelScore are used to evaluate model fit to cryo-EM maps, while local map resolution tools help identify regions of lower resolution. ChimeraX also supports the analysis of additional experimental data, such as crosslinking and electron tomography, through extensions like XMAS and ArtiaX. The software is capable of building and modifying atomic structures independently of experimental data, and can prepare them for computational pipelines involving molecular docking or dynamics simulations. The software is easily extendable using Python and provides a user-friendly interface for integrating various steps in model building. ChimeraX is available for macOS, Windows, and Linux, and offers comprehensive documentation, tutorials, and contributed extensions. The software is widely used by the cryo-EM community for its robust visualization and analysis capabilities, and its integration of new methods and tools helps reduce the time and effort required to create accurate models. The authors of this article have contributed to the development and refinement of ChimeraX, and the software is supported by various funding sources, including the National Institutes of Health and the Chan Zuckerberg Initiative.