Human language learning differs significantly across individuals in the process and ultimate attainment. Although decades of research exploring the neural substrates of language learning have identified distinct and overlapping neural networks subserving learning of different components, the neural mechanisms that drive the large inter-individual differences are still far from being understood. Here we examine to what extent the neural dynamics of multiple brain networks in men and women across sessions of training contribute to explaining individual differences in learning multiple linguistic components (i.e., vocabulary, morphology, and phrase and sentence structures) of an artificial language in a seven-day training and imaging paradigm with functional Magnetic Resonance Imaging. With machine-learning and predictive modeling, neural activation patterns across training sessions were highly predictive of individual learning success profiles derived from the four components. We identified four neural learn...