RNA viruses, as significant pathogens, have higher‐order structural elements that impact viral infection and transmission by regulating translation, replication, and virus‐host interactions. Methods for investigating RNA structures involve both traditional experimental techniques and computational biology approaches. Notably, recent progress in machine learning and deep learning, and the combination with high‐throughput sequencing data, has substantially enhanced the accuracy with which RNA structures are predicted. The combination of multiple technologies will shed light on the special structures and functions of viral RNAs, thereby providing novel strategies for designing RNA‐structure‐targeted antiviral therapeutics. This review outlines recent advances in research on the genomic structures of RNA viruses and summarizes the current studies and major discoveries in this field. Critical technological breakthroughs in interpretations of RNA structures are highlighted while priorities of future research are predicted.