Children’s early ability to implicitly learn the underlying patterns in their environment, also known as statistical learning (SL), is a crucial component of typical cognitive development. SL is essential for visual perception and language processing in infants, children, and adults. However, previous studies have not explored the association between children’s environment and underlying neural mechanisms of SL ability in children. Socioeconomic status (SES) is one of the most important indicators of the quality of this environment. Children who live in low SES families have less exposure to cognitive and linguistic stimulation and show atypical structural and functional neural patterns compared to those with high SES. In this study, I explored the influence of SES (i.e., parental education level and household income) on gray matter volume of brain regions involved in SL ability in 232 healthy children ages 5-12 years recruited by the Human Connectome Project. These brain regions consisted of sensory/perceptual (primary visual and auditory cortices) and frontal/subcortical (Broca’s area and caudate nucleus) regions previously reported to be involved in SL. In addition, I investigated the role of age in the potential interaction of SES with differences in these brain structures. The findings showed neither SES measure to be a predictor of variance in the volume of sensory/perceptual brain regions. In contrast, parental education was a strong predictor of variance in volume of one of the frontal/subcortical regions, namely caudate nucleus. Age, however, did not influence the association between SES measures and either region of interest. This study is the first to explore the influence of various SES factors on gray matter volume of sensory/perceptual and frontal/subcortical regions involved in SL in children.