The coastal wetland of the Yellow River Estuary, one of China’s largest wetlands, is essential for biodiversity conservation and ecosystem services. The diversity of zoobenthos is a critical indicator of ecosystem health and water quality, supporting the food chain and maintaining the stability of biological networks. However, the community characteristics of zoobenthos in this coastal wetland are poorly understood. This study utilized eDNA metabarcoding to assess the diversity and community structure of zoobenthos in the Yellow River Estuary Coastal Wetland. Zoobenthos from 174 families were identified, with 307 species recognized at the generic level, significantly more than those identified through traditional morpho-taxonomic approaches. Salinity emerged as a crucial factor in shaping these ecosystems, with brackish water exhibiting the lowest species richness compared to that of freshwater and seawater. Environmental factors such as salinity, organic matter, and nutrient elements significantly influence the composition and distribution of zoobenthos. Specifically, cations, particularly Mg²⁺ and Ca²⁺, have a more substantial impact on zoobenthos than anions. These findings underscores the effectiveness of eDNA metabarcoding in providing a comprehensive assessment of biodiversity and offers insights into the ecological dynamics and environmental factors shaping zoobenthos communities. Still, enhancing eDNA collection efficiency and expanding the reference database are necessary to improve accuracy and effectiveness in future ecological monitoring of zoobenthos.