Although much work has been done to elucidate the regulatory mechanism of miRNAs by associating miRNAs with mRNAs, their precise functions are still largely unknown. Latent dirichlet allocation (LDA) topic model is thus proposed to infer regulatory modules of miRNAs and their targets mRNAs for specific biological conditions. The proposed model firstly uses Welch′s t-test to mine differentially expressed miRNAs and mRNAs, and then a collapsed Gibbs sampling method is utilized to estimate parameters. The results on epithelial to mesenchymal transition (EMT) data sets show that the inferred functional miRNA mRNA regulatory modules (FMRMs) can construct regulatory relationships between miRNAs and mRNAs in different biological conditions, and give new insights into EMT biological process and miRNA targets therapy. Compared with K-means clustering algorithm, LDA topic model is more efficient in mining FMRMs.