Infants learn their native language by interacting with their caregivers and environments and without explicit language instruction. While the process may superficially appear almost as effortless, acquiring a language from sensorimotor experiences with the external world is an enormously complicated cognitive task. While decades of research have provided us with several bits and pieces of knowledge on infant language development, we still lack holistic, accurate, and testable models of how the infants succeed in bootstrapping their language skills. In this talk, I will introduce the concept of computational modeling of early language development and motivate its potential in developing holistic accounts of the learning process. I will then describe the theoretical basis we use in our own modeling research. I end with a few examples of recent modeling studies that show how linguistic structure of spoken language can be acquired from auditory or audiovisual experiences of language with general predictive statistical learning mechanisms. The examples also illustrate how the learning can take place without the learner ever explicitly targeting at linguistic units, such as phonemes or words.