This study investigates the biological processes that support children’s social skill development in the framework of familial interactions. The study looks at multidimensional datasets, such as physiological biomarkers, brain activity, and observed behaviors, using a attentive adversarial deep subspace clustering (SAADSC) algorithm to find patterns that connect competences to family dynamics. The results show that brain configurations that support social functioning are consistently linked to high levels of family cohesion. Furthermore, the accuracy of behavioral outcome predictions is significreased by include physiological factors in the analytical model, such as heart rate variability and cortisol concentration. Through a datadriven, interdisciplinary lens, this integrated methodology provides important insights for developmental psychology and social neuroscience by revealing how biological systems moderate environmental impacts.