Body segment inertial parameters (BSIPs) are critical for human movement analysis. However, child-specific BSIPs remains limited. This study aimed to develop regression models for BSIPs (mass, CoM-position, and moments of inertia) using 3D body scans from 688 children aged 2.9–12.7 years. A 3D scanning system was used to capture body surfaces as point clouds, which were automatically processed to generate segmented, personalized volumetric body meshes with embedded segment coordinate systems. These meshes were then used to compute 3D BSIPs, which were normalized (relative to body mass and corresponding segment length) and fitted by regression models separately for males and females. The regression models demonstrated high predictive accuracy for normalized mass and moderate-to-good accuracy for normalized CoM-positions and radii of gyration. Age-related changes were observed as reductions in normalized mass for the head-neck and abdomen, alongside increases for the thigh. Normalized CoM-positions shifted posteriorly for the abdomen, anteriorly for the thigh, and proximally for the forearm. Normalized radii of gyration declined across all directions, particularly for the hand and thigh. This work provides the first comprehensive BSIP regressions for a large, gender-balanced cohort of children up to 12 years old, addressing limitations in prior research with a fully automated approach. These regressions are expected to advance biomechanical modeling and enhance movement analysis in pediatric populations.