The metabolic activities of microbial communities play a defining role in the evolution and persistence of life on Earth, driving redox reactions that give rise to global biogeochemical cycles. Community metabolism emerges from a hierarchy of processes, including gene expression, ecological interactions, and environmental factors. In wild communities, gene content is correlated with environmental context, but predicting metabolite dynamics from genomes remains elusive. Here, we show, for the process of denitrification, that metabolite dynamics of a community are predictable from the genes each member of the community possesses. A simple linear regression reveals a sparse and generalizable mapping from gene content to metabolite dynamics for genomically diverse bacteria. A consumer-resource model correctly predicts community metabolite dynamics from single-strain phenotypes. Our results demonstrate that the conserved impacts of metabolic genes can predict community metabolite dynamics, enabling the prediction of metabolite dynamics from metagenomes, designing denitrifying communities, and discovering how genome evolution impacts metabolism. Display omitted •Metabolite fluxes in microbial communities are predictable from individual genotypes•A diverse collection of 79 bacterial isolates was sequenced and phenotyped•Gene presence and absence predict metabolic phenotypes of isolates via regression•A consumer-resource model predicts community metabolite fluxes from phenotypes The presence or absence of specific genes within communities of wild bacterial isolates is sufficient to predict community-level metabolite dynamics without detailed knowledge of pathway regulation or complex ecological processes.