Abstract Reverse transcription quantitative real-time PCR (RT-qPCR) is esteemed for its precision and reliability, positioning it as the standard for evaluating gene expression. Selecting suitable reference genes is crucial for acquiring accurate data on target gene expression. However, identifying appropriate reference genes for specific rice tissues or growth conditions has been a challenge. To overcome this, we introduce the Rice Reference Genes (RRG) tool ( https://www.rrgenes.com/ ), which assists researchers in selecting reference genes for diverse experimental conditions in rice. This tool utilizes 4404 rice-derived RNA-seq datasets, categorized by five tissue types—leaf, root, seedling, panicle, and seed—and seven stress conditions (cold, disease, drought, heat, hormone, metal, and salt), along with corresponding control groups (mock). In this research, we employed the RRG web-based tool to identify candidate reference genes in rice leaves, roots, and seedlings exposed to salt and drought stress. These candidates were rigorously tested against conventionally established reference genes, confirming their accuracy and reliability. The RRG tool is designed to be user-friendly, allowing even those with limited experience to efficiently select optimal reference genes in rice with ease.