Neuronal oscillations are comprised of rhythmic fluctuations of excitability that are synchronized in ensembles of neurons and thus function as temporal filters that dynamically organize sensory processing. When perception relies on anticipatory mechanisms, ongoing oscillations also provide a neurophysiological substrate for temporal prediction. In this article, we review evidence for this account with a focus on auditory perception. We argue that such "oscillatory temporal predictions" can selectively amplify neuronal sensitivity to inputs that occur in a predicted, task-relevant rhythm and optimize temporal selection. We elaborate this argument for a prototypic example, speech processing, where information is present at multiple time scales, with delta, theta, and low-gamma oscillations being specifically and simultaneously engaged, enabling multiplexing. We then consider the origin of temporal predictions, specifically the idea that the motor system is involved in the generation of such prior information. Finally, we place temporal predictions in the general context of internal models, discussing how they interact with feature-based or spatial predictions. We propose that complementary predictions interact synergistically according to a dominance hierarchy, shaping perception in the form of a multidimensional filter mechanism.