Bone, a pivotal structural organ, is susceptible to disorders with profound health implications. The investigation of gene expression in bone tissue is imperative, particularly within the context of metabolic diseases such as obesity and diabetes that augment the susceptibility to bone fractures. The objective of this study is to identify a set of internal control genes for the analysis of gene expression. This study employs reverse transcription-quantitative real-time polymerase chain reaction (RT-qPCR) to assess gene expression in bone tissue. We selected fourteen housekeeping genes and assessed their stability in the cortical bone of mouse models for obesity and diabetes using four well-established algorithms (GeNorm, BestKeeper, NormFinder, and the comparative Delta Ct method). We identified Rpl13a as the mostly stably expressed reference gene in cortical bone tissue from mouse models of obesity and diabetes (db/db), while Gapdh was found to be the most stable reference gene in another diabetes model, KKAy mice. Additionally, Ef1a, Ppia, Rplp0, and Rpl22 were identified as alternative genes suitable for normalizing gene expression in cortical bone from obesity and diabetes mouse models. These findings enhance RT-qPCR accuracy and reliability, offering a strategic guide to select reference gene for studying bone tissue gene expression in metabolic disorders.