Plant microRNAs (miRNAs) are tiny, non-coding RNAs that regulate the biological pathways either by inducing translational repression or messenger RNA decay. The advent of sequencing technologies increases the number of biological tools and computational methods to identify miRNAs with their targets inside the genome and transcriptome. In this study, we present a rapid curation software tool, the so-called miRCurator, which filters out unwanted microRNA candidates based on three significant criteria: (1) the pre-miRNA sequence should be deprived of multi-branched loops; (2) less than four mismatches on between mature miRNA and miRNA* strand are allowed; (3) no mismatches at DICER cut points are permitted on a mature miRNA strand. miRCurator is a stand-alone user-friendly package that does not rely on cutting-edge computing platforms. We have examined our tool on different organisms, which are shown as case studies, and it was able to successfully identify all the unwanted miRNA candidates. The developed tool helps to identify genuine miRNAs and provides reliable outcomes in an automated fashion by eliminating false-positive predictions.