Research suggests that infants use statistical regularities in linguistic input to identify and learn a range of linguistic structures, from the sounds of language (e.g., native‐language speech sounds, word boundaries in continuous speech) to aspects of grammatical structure (e.g., lexical categories like nouns and verbs, basic aspects of syntax). In this article, I review the literature on statistical language learning in infants and raise questions about why infants are sensitive to statistical regularities. In doing so, I consider the relationship among statistical learning, prediction, and reducing uncertainty in infancy.