Abstract The Discriminative Lexicon is a theory of the mental lexicon that brings together insights from various other theories: words are the relevant cognitive units in morphology, the meaning of a word is represented by its distribution in utterances, word forms and their meaning are learned by minimizing prediction errors, and fully connected networks successfully capture language learning. In this article we model comprehension and production of Kinyarwanda verb forms in the Discriminative Lexicon model. Kinyarwanda is a highly inflectional language, and therefore particularly interesting, because its paradigms are almost unlimited in size. Can knowledge of its enormous paradigms be modeled only on the basis of words? To answer this question we modeled a data set of 11,528 verb forms, hand-annotated for meaning and their grammatical functions, in the Linear Discriminative Learning (LDL), a two-layered, fully connected computational implementation of the Discriminative Lexicon model. We also extracted 573 verbs from our data set for which meanings are available that are based on empirical word embeddings obtained from large text corpora, and modeled them in LDL. Both comprehension and production is learned accurately: Kinyarwanda verb forms can be comprehended and produced relying on words as cognitive units, in a two-layered network, in which prediction errors are minimized.