This review article 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 templates are used for alignment and analysis, while atlases capture anatomical or physiological structures in a reference space. The review focuses on 18 prenatal brain atlases and 3 datasets, detailing their construction methods, content, and applications. Atlases are categorized into single-subject, multi-subject, and probabilistic types, with the latter being the most common due to their ability to incorporate prior knowledge and facilitate population-based analyses. The article also discusses the challenges in constructing fetal MRI atlases, such as fetal movement and the rapid brain development during pregnancy. It highlights the use of advanced reconstruction algorithms to improve image quality and the importance of spatio-temporal atlases for capturing brain changes over time. The review concludes by discussing the future directions in fetal brain research, including the integration of multimodal imaging techniques and the potential of AI-based algorithms in advancing the field.This review article 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 templates are used for alignment and analysis, while atlases capture anatomical or physiological structures in a reference space. The review focuses on 18 prenatal brain atlases and 3 datasets, detailing their construction methods, content, and applications. Atlases are categorized into single-subject, multi-subject, and probabilistic types, with the latter being the most common due to their ability to incorporate prior knowledge and facilitate population-based analyses. The article also discusses the challenges in constructing fetal MRI atlases, such as fetal movement and the rapid brain development during pregnancy. It highlights the use of advanced reconstruction algorithms to improve image quality and the importance of spatio-temporal atlases for capturing brain changes over time. The review concludes by discussing the future directions in fetal brain research, including the integration of multimodal imaging techniques and the potential of AI-based algorithms in advancing the field.