Maternal antenatal depression (AD) is a nonpsychotic depressive episode during pregnancy that can harm both the pregnant woman and the fetus. This study aimed to investigate the intrinsic interrelationships between AD and its influencing factors by constructing a path model. This survey-based cross-sectional study included 1071 pregnant women who underwent pregnancy examinations in three hospitals in Nantong City, China, between February and June 2023. General information and information regarding maternal AD, pregnancy stress, prenatal anxiety, social support, marital satisfaction, sleep quality, and resilience were collected. Multiple linear regression analysis using SPSS 25.0 was employed to determine the factors influencing pregnancy depression, and Amos25.0 was used to construct a structural equation model. AD incidence was 19.4% (208/1071). The independent risk factors affecting AD in pregnant women have been integrated into the established path analysis model. The model demonstrated a good fit (χ2/DF = 1.238, comparative fit index = 0.999, goodness-of-fit index = 0.998, normed fit index = 0.996, adjusted goodness-of-fit index = 0.990, incremental fit index = 0.999, and root mean square error of approximation = 0.015). While prenatal anxiety (0.230) and hyperthyroidism (0.048) only had direct effects on AD, mental resilience was the biggest factor affecting AD, followed by pregnancy stress, marital satisfaction, prenatal anxiety, sleep quality, social support, and hyperthyroidism. Improved mental resilience, social support, sleep quality, and marital satisfaction; reduced pregnancy stress and prenatal anxiety; and effective hyperthyroidism treatment might reduce AD. This study underscored the significance of delivering actionable strategies and tangible assistance to pregnant women to reduce AD.