Background: Growing evidences suggest that microRNAs (miRNAs) can efficiently regulate gene expression at intracellular and extracellular levels. It has been previously reported that plant/food-derived miRNAs are highly enriched in human serum or serum from phytophagous animals, and they are responsible for regulating mammalian gene expression. Thus, miRNAs could function as active signaling molecules, which carry information across distinct species or even kingdoms. However, the mode of miRNA shuttling among various organisms is still a mystery to unravel. The intra and inter kingdom miRNA transfer has boosted up the hypothesis about the potential impact of plant or animal miRNAs on each other. To our knowledge, the software for analyzing cross-kingdom miRNA-targets is lacking. Results: We have developed a web-tool “IIKmTA: Inter and Intra Kingdom miRNA-Target Analyzer” utilizing a database; the data of which have been collected from another web server. Here, user can analyze the targeting potential of (i) plant miRNAs on animal UTRs (Untranslated regions), and vice versa (i.e., inter kingdom), (ii) plant miRNAs on plant UTRs and animal miRNAs on animal UTRs (i.e., intra kingdom). Further, user can analyze (i) miRNAs to targets, (ii) targets to miRNAs, and (iii) miRNA sets targeting sets of targets. For a wide variety of animal and plant species, IIKmTA can identify the miRNA binding sites in the probable target UTRs. Moreover, GC% and AU% of miRNAs will be calculated. All the results can be saved as.csv file. Conclusions: Recent researches identified miRNAs in plants and human secretions and their role in regulating the human genes. Such findings indicate the therapeutic role of secretory miRNAs of such plants which exhibits medicinal value and in near future many diseases may be treated by consumption of these plant miRNAs through food. Using our newly developed database and analyzing tool, one can easily determine the different relationships between miRNAs and their targets across kingdoms. IIKmTA is freely available at http://www.bioinformatics.org/iikmta/. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.