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Reference genes for normalization of reverse transcription quantitative real-time PCR (RT-qPCR) experiments were selected and evaluated for drought-stressed leaves of three European Quercus species (Q. ilex, Q. pubescens, and Q. robur). A drought experiment was conducted over the course of 2years. In the first year, a comparative transcriptome analysis was conducted between control and drought-stressed plants in all three species. Based on this analysis, six genes which showed a low fold change and low individual variation of normalized expression values were selected as novel candidate reference genes. The six novel candidate genes were homologs of the serine/threonineprotein kinase At1g54610 (At1g54610), ATP synthase gamma chain (ATPC1), far-red elongated hypocotyl 3-like (FHY3), 50S ribosomal protein L13 (RPL13), serine/threonine-protein phosphatise PP1 (TOPP2), and splicing factor U2af small subunit B-like (U2AF35B). As a control, the two classical candidate reference genes glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and elongation factor 1 alpha (EF1a) were included. Cross-species primers were designed for all candidate reference genes. The reference genes were evaluated in samples from three dates in the second year of the drought experiment. Four different algorithms (Bestkeeper, the comparative Ct method, geNorm, and Normfinder) were utilized to analyze expression stability. The results of the algorithms were summarized, and the most stable genes and optimal number of reference genes were identified for every species. These results demonstrated that, in each species, at least four of the novel reference genes are more stably expressed than the classical reference genes and that two reference genes are the optimal number for each species. One novel reference gene, At1g54610, was found to be among the two most stable reference genes across all three species; the second most stable gene was found to be TOPP2 in Q. ilex, U2AF35B in Q. pubescens, and FHY3 in Q. robur. Reference genes are crucial to normalize qPCR data and to identify stress-responsive genes, e.g., in the context of a search for drought-tolerant Quercus genotypes able to withstand the predicted increase of drought events in large parts of Europe during climate change.