Microbial cells in natural environments are typically embedded in microbial communities consisting of few to many different species. Close proximity and high diversity of neighboring cells facilitate manifold interactions on several layers, from substrate competition, exchange of genetic material, to metabolic cross-feeding. The complexity of these ecological interaction networks makes microbiomes notoriously difficult to study. While microbiome dynamics can routinely be elucidated by meta-omics technologies, pinpointing mechanisms driving these observed dynamics remains a challenge. Mechanistic mathematical modeling with its ability to focus on individual interactions and exploring their isolated impact on overall dynamics has emerged as a suitable tool in this context. Here, we use μbialSim, an open-source simulator that extends the Flux Balance Analysis approach to microbial communities, considering substrate competition and metabolic cross-feeding but neglecting any other microbial interactions. Assuming a well-mixed bioreactor environment, simulated trajectories enable the analysis of growth behavior of individual microbiome members, dynamics of intracellular enzymatic fluxes across all species, as well as the analysis of cross-feeding behavior and how it changes over time. The MATLAB implementation of μbialSim is available from https://github.com/fcentler/microbialSim .