This review provides a comprehensive overview of fetal brain MRI atlases and datasets, highlighting their importance in understanding prenatal brain development. The authors clarify the distinction between "brain template" and "brain atlas," emphasizing that while they are often used interchangeably, they have distinct roles in research and clinical practice. The review discusses the major structures and neurodevelopmental milestones in fetal brain ontogenesis and systematically reviews 18 prenatal brain atlases and 3 datasets. It also addresses the clinical, research, and ethical implications of prenatal neuroimaging. Fetal brain development involves complex processes of growth and organization crucial for the development of brain circuits and neural connections. Prenatal brain imaging and post-processing using modern tools are a cutting-edge field that significantly contribute to understanding fetal development. The review focuses on the prenatal period and screens recently introduced MRI atlases, as scientific and clinical interest in fetal development is increasing, and neuroimaging techniques such as diffusion MRI have advanced. The review categorizes fetal brain atlases into three main types: single-subject, multi-subject, and probabilistic. Probabilistic atlases are particularly useful for capturing brain changes during pregnancy, as they reflect anatomical variability in the population. The review identifies 18 probabilistic fetal brain atlases and 3 datasets, with 18 being publicly available. These atlases are defined based on gestational age (GA) and include various types of images, such as T2-weighted, diffusion-weighted imaging (DWI), and surface images. The review also discusses the challenges in constructing fetal MRI brain atlases, including the difficulty of fetal MRI due to the size of the brain, the mother's body in the scanner, and fetal movements. Additionally, the brain undergoes significant plasticity and growth during the prenatal period, necessitating specific brain atlases for narrow temporal windows. The review highlights the importance of spatio-temporal atlases in assessing potential deviations in prenatal neurodevelopment trajectories and provides a reference space for population-based analyses. The authors also emphasize the role of publicly available datasets in developing and benchmarking new methods for automated fetal brain labeling. The review concludes that generating multimodal spatiotemporal fetal brain atlases that combine multiple MRI-derived maps in the same anatomical space across a wide gestational age range is a future challenge in fetal brain research. The review also discusses the importance of combining functional and anatomical imaging approaches to better characterize the relationship between brain structures and functions.This review provides a comprehensive overview of fetal brain MRI atlases and datasets, highlighting their importance in understanding prenatal brain development. The authors clarify the distinction between "brain template" and "brain atlas," emphasizing that while they are often used interchangeably, they have distinct roles in research and clinical practice. The review discusses the major structures and neurodevelopmental milestones in fetal brain ontogenesis and systematically reviews 18 prenatal brain atlases and 3 datasets. It also addresses the clinical, research, and ethical implications of prenatal neuroimaging. Fetal brain development involves complex processes of growth and organization crucial for the development of brain circuits and neural connections. Prenatal brain imaging and post-processing using modern tools are a cutting-edge field that significantly contribute to understanding fetal development. The review focuses on the prenatal period and screens recently introduced MRI atlases, as scientific and clinical interest in fetal development is increasing, and neuroimaging techniques such as diffusion MRI have advanced. The review categorizes fetal brain atlases into three main types: single-subject, multi-subject, and probabilistic. Probabilistic atlases are particularly useful for capturing brain changes during pregnancy, as they reflect anatomical variability in the population. The review identifies 18 probabilistic fetal brain atlases and 3 datasets, with 18 being publicly available. These atlases are defined based on gestational age (GA) and include various types of images, such as T2-weighted, diffusion-weighted imaging (DWI), and surface images. The review also discusses the challenges in constructing fetal MRI brain atlases, including the difficulty of fetal MRI due to the size of the brain, the mother's body in the scanner, and fetal movements. Additionally, the brain undergoes significant plasticity and growth during the prenatal period, necessitating specific brain atlases for narrow temporal windows. The review highlights the importance of spatio-temporal atlases in assessing potential deviations in prenatal neurodevelopment trajectories and provides a reference space for population-based analyses. The authors also emphasize the role of publicly available datasets in developing and benchmarking new methods for automated fetal brain labeling. The review concludes that generating multimodal spatiotemporal fetal brain atlases that combine multiple MRI-derived maps in the same anatomical space across a wide gestational age range is a future challenge in fetal brain research. The review also discusses the importance of combining functional and anatomical imaging approaches to better characterize the relationship between brain structures and functions.