In forensic molecular pathology, quantitative real-time polymerase chain reaction (RT-qPCR) provides a rapid and sensitive method to investigate functional changes in the death process. Accurate and reliable relative RT-qPCR requires ideal amplification efficiencies of target and reference genes. However, the amplification efficiency, changing during PCR, may be overestimated by the traditional standard curve method. No single gene meets the criteria of an ideal endogenous reference. Therefore, it is necessary to select suitable reference genes for specific requirements. The present study evaluated 32 potential reference genes in the human brain of 15 forensic autopsy cases using three different statistical algorithms, geNorm, NormFinder, and BestKeeper. On RT-qPCR data analyses using a completely objective and noise-resistant algorithm (Real-time PCR Miner), 24 genes met standard efficiency criteria. Validation of their stability and suitability as reference genes using geNorm suggested IPO8 and POLR2A as the most stable ones, and NormFinder indicated that IPO8 and POP4 had the highest expression stabilities, while BestKeeper highlighted ABL1 and ELF1 as reference genes with the least overall variation. Combining these three algorithms suggested the genes IPO8, POLR2A, and PES1 as stable endogenous references in RT-qPCR analysis of human brain samples, with YWHAZ, PPIA, HPRT1, and TBP being the least stable ones. These findings are inconsistent with those of previous studies. Moreover, the relative stability of target and reference genes remains unknown. These observations suggest that suitable reference genes should be selected on the basis of specific requirements, experiment conditions, and the characteristics of target genes in practical applications.