SUMMARY: In recent years, phased small interfering RNA has been found to play crucial roles in many biological processes in plants. However, efficiently predicting phasiRNA regulatory cascades with computational methods is still challenging. Here, we introduce PhasiHunter, a phasiRNA regulatory network prediction tool that has several distinctive features compared to existing tools: (i) PhasiHunter employs two major phasiRNA prediction algorithms, namely phase score and hypergeometric distribution-based methods, to ensure the integrity and accuracy of prediction; (ii) PhasiHunter can identify phasiRNAs and their regulatory networks based on multiple reference sequences and the predicted results can be automatically integrated; (iii) PhasiHunter can efficiently identify the phasiRNAs generated through alternative splicing events; and (iv) the excellent data structure and parallel computing architecture allow PhasiHunter to predict phasiRNAs and their regulatory pathways with high efficiency. AVAILABILITY AND IMPLEMENTATION: PhasiHunter is an open-source tool that is available at https://github.com/HuangLab-CBI/PhasiHunter.