Abstract: Promoting the synergistic development of digital rural construction and the green transformation of animal husbandry is a key pathway to advancing smart animal husbandry. Based on panel data from 31 provinces in China from 2013 to 2022, this study employs the coupling coordination degree model, social network analysis (SNA), and the quadratic assignment procedure (QAP) to systematically analyze the spatiotemporal patterns, spatial correlation network characteristics, and driving mechanisms of digital rural construction and the green transformation of animal husbandry. The results show that: 1) The coupling coordination degree has steadily improved, shifting from near imbalance to primary coordination, and presents a spatial distribution pattern of higher levels in the east and lower levels in the west; 2) The overall spatial network structure has become increasingly complex, with non-adjacent provinces achieving cross-regional linkages beyond geographical constraints; 3) Significant spatial heterogeneity exists in individual network structures, with developed eastern provinces consistently occupying core positions in the network, while western border provinces remain at the periphery; 4) Geographical proximity and differences in economic development levels significantly promote the formation of spatial correlation networks, whereas disparities in technological innovation capacity and human capital levels have an inhibiting effect. Based on these findings, it is recommended to narrow regional development gaps, promote cross-regional collaboration, and strengthen the driving mechanisms of spatial correlation to accelerate the coordinated digital and green transformation of animal husbandry.