Plant microRNAs (miRNA) target recognition mechanism was once thought to be simple and straightforward, i.e. through perfect reverse complementary matching; therefore, very few target prediction tools and algorithms were developed for plants as compared to those for animals. However, the discovery of transcription suppression and the more recent observation of widespread translational regulation by miRNAs highlight the enormous diversity and complexity of gene regulation in plant systems. This, in turn, necessitates the need for advanced computational tools/algorithms for comprehensive miRNA target analysis to help understand miRNA regulatory mechanisms. Yet, advanced/comprehensive plant miRNA target analysis tools are still lacking despite the desirability and importance of such tools, especially the ability of predicting translational inhibition and integrating transcriptome data. This review focuses on recent progress in plant miRNA target recognition mechanism, principles of target prediction based on these understandings, comparison of current prediction tools and algorithms for plant miRNA target analysis and the outlook for future directions in the development of plant miRNA target tools and algorithms.