MicroRNAs (miRNAs) are small non-coding RNAs of approximately 22 nucleotides in length, which play important roles in regulating gene expression post-transcriptionally. Several computational methods and algorithms have been developed to predict miRNA targets. In this study, we described a method that can be used to integrate miRNA target prediction data from multiple sources and gene expression data to predict target genes of particular miRNAs. We used hsa-miR-375 as an example to test the feasibility of our method. A total of 5645 target genes of hsa-miR-375 were identified from five prediction programs, and among them, 2440 target genes were shared by at least 2 of these 5 programs. By using our method, the number was further reduced to 149 and 5 of the 149 target genes had been validated by previous study. This is a simple yet highly effective approach.