A computational model of binaural lateralization is described. An accurate model of the auditory periphery feeds a tonotopically organized multichannel cross-correlation mechanism. Lateralization predictions are made on the basis of the integrated activity across frequency channels. The model explicitly weights cross-correlation peaks closer to the center preferentially, and effectively weights information that is consistent across frequencies more heavily because they have a greater impact in the across frequency integration. This model is complementary to the weighted-image model of Stern et al. [J. Acoust. Soc. Am. 84, 156–165 (1988)], although the model described in this paper is physiologically more plausible, is simpler, and is more versatile in the range of input stimuli that are possible.