Quantitative real-time PCR (qPCR) is a powerful tool to measure gene expression levels. Accurate and reproducible results are dependent on the correct choice of the reference genes for data normalization. To date, screenings evaluating candidate reference gene stability for expression studies in maize have not been reported. In the present work, we analyzed the expression patterns of 12 genes in a set of 20 maize samples, obtained from different tissues of plants grown at various experimental conditions. Using genorm(PLUS), NormFinder and BestKeeper algorithms, the expression stability of three "classical" reference genes, such as ACT, TUB and 18S rRNA, and the newly identified candidates, was assessed. With respect to the algorithms, our results showed similar performance among genorm(PLUS), NormFinder and BestKeeper in evaluating the suitability of reference genes. Our data therefore showed that the currently and widely used reference genes for data normalization in maize were not the most stable expressed transcripts. Five of the new putative reference genes (CUL, FPGS, LUG, MEP and UBCP) exhibited the highest expression stability according to all algorithms. In conclusion, with this study, we provide a list of validated reference genes and their relative primer sequences to conduct reliable qPCR experiments in maize.