During the second-to-third trimester, the neuronal pathways of the fetal brain experience rapid development, resulting in the complex architecture of the inter-wired network at birth. While diffusion MRI-based tractography has been employed to study the prenatal development of structural connectivity network (SCN) in preterm neonatal and post-mortem fetal brains, the in-utero development of SCN in the normal fetal brain remains largely unknown. In this study, we utilized in-utero dMRI data from human fetuses of both sexes between 26 to 38 gestational weeks to investigate the developmental trajectories of the fetal brain SCN, focusing on intra-hemispheric connections. Our analysis revealed significant increases in global efficiency, mean local efficiency, and clustering coefficient, along with significant decrease in shortest path length, while small-worldness persisted during the studied period, revealing balanced network integration and segregation. Widespread short-ranged connectivity strengthened significantly. The nodal strength developed in a posterior-to-anterior and medial-to-lateral order, reflecting a spatiotemporal gradient in cortical network connectivity development. Moreover, we observed distinct lateralization patterns in the fetal brain SCN. Globally, there was a leftward lateralization in network efficiency, clustering coefficient, and small-worldness. The regional lateralization patterns in most language, motor, and visual-related areas were consistent with prior knowledge, except for the Wernicke’s area, indicating lateralized brain wiring is an innate property of the human brain starting from the fetal period. Our findings provided a comprehensive view of the development of the fetal brain SCN and its lateralization, as a normative template that may be used to characterize atypical development.Significance StatementWe studied the normal development of intra-hemispheric cortico-cortical structural connectivity networks (SCNs) of the fetal brain from 26 to 38 gestational weeks using in-utero diffusion MRI data. Graph-theory-based analysis revealed significant enhancement in network efficiency and clustering, as well as persisted small-worldness with age, revealing balanced integration and segregation in the fetal brain SCN during the studied period, supported by regional developmental patterns. Leftward lateralization in network efficiency, clustering coefficient and small-worldness was observed. Regional lateralization patterns in most language, motor, and visual-related areas were consistent with prior knowledge. We also summarized the challenges of investigating the fetal brain SCN development, and provided suggestions for future studies.