MicroRNAs (miRNAs) are short single-stranded non-coding RNA molecules, which are involved in regulation of main biological processes, such as apoptosis, cell proliferation and differentiation, through sequence-specific interaction with target mRNAs. In this study we propose a workflow for predicting miRNAs function by analyzing the structure of the network of their target genes. This workflow was applied to study the functional role of miR-375 in the heart muscle (myocardium), since this miRNA was previously shown to be associated with heart diseases and data on its function in myocardium are mostly unclear. We identified PIK3CA, RHOA, MAPK3, PAFAH1B1, CTNNB1, MYC, PRKCA, ERBB2, and CDC42 as key genes in the miR-375 regulated network and predicted the possible function of miR-375 in the heart muscle, consisting mainly in the regulation of the Rho-GTPases-dependent signalling pathways. We implemented our algorithm for miRNA function prediction into Python module, which is available at GitHub (https://github.com/GJOsmak/miRNET).