Abstract: In this study, we utilized comprehensive survey data of fishery resources and environments in Haizhou Bay from 2013 to 2020. We employed a Support vector machine (SVM) model to analyze the spatial distribution characteristics of S. esculenta in Haizhou Bay and assess the impacts of various environmental factors. This analysis involved cross-validation and the use of evaluation indicators, including the Akaike Information Criterion (AIC). Results showed that water depth was the most important factor, followed by bottom salinity, bottom sea temperature and offshore distance. The relative density of S. esculenta exhibited a negative correlation with temperature but a positive correlation with salinity. Additionally, the abundance of S. esculenta increased firstly with water depth and offshore distance, and then decreased. The relative density of S. esculenta was relatively large at water depth of 27 m and offshore distance of about 40 km. The distribution pattern showed a higher abundance in the eastern and north-central areas and a lower abundance in the south western coastal waters. This study contributes to our understanding of the spatial distribution of S. esculenta in Haizhou Bay, and provides reference for the rational utilization and scientific conservation of its resources.