Children acquire complex concepts like dog earlier than simple concepts like brown, even though our best neuroscientific theories suggest that learning the former is harder than learning the latter and, thus, should take more time (Markus Werning). This is the complex-first paradox. We present a novel solution to the complex-first paradox. Our solution builds on a generalization of Fei Xu and Joshua B. Tenenbaum’s Bayesian model of word learning. By focusing on a rational theory of concept learning, we show that it is easier to infer the meaning of complex concepts than that of simple concepts.