Background: Graves' disease (GD), one of the most common forms of autoimmune thyroid disorders, is characterized by hyperthyroidism caused by antibodies (Abs) against the extracellular A-subunit of the thyrotropin receptor (TSHR). Various approaches have been used to create mouse models of GD, including transfected fibroblasts and immunization with plasmids or adenoviruses expressing human TSHR A-subunit (hTSHR A-subunit). These models, however, require repeated immunization and produce inconsistent results. In this study, we established a novel Cre-loxP system-based mouse model that is able to generate the hTSHR A-subunit, mimicking human GD, and characterized the histological changes in Graves' orbitopathy (GO) progression after a single injection. Materials and Methods: A Cre-loxP system-based mouse model was constructed by inserting the CAG-loxP-STOP-loxP-hTSHR A-subunit cassette into the Rosa26 locus of the mouse genome. Conditional expression of the hTSHR A-subunit was successfully achieved by intramuscular injection of the transactivator of transcription-Cre recombinase (GD mice). Blood tests for anti-TSHR Abs and the total thyroxine (T4) level were performed. Magnetic resonance imaging (MRI) was used to monitor morphological changes in the eyes. A histological examination of the thyroid gland and retrobulbar tissues was performed to observe pathological changes. Results: Twenty-four (8 control and 16 GD) mice were investigated. All GD mice exhibited higher levels of TSHR Abs compared with the control group. Moreover, more than 80% of the mouse models showed elevated T4 levels accompanied by thyroid goiter. MRI analysis revealed an increased volume of retrobulbar tissue, while immunohistochemical staining of orbital tissues exhibited macrophage infiltration and muscle fibrosis in the GD mice, contrasting with the control group. Conclusions: Our novel mouse model for GD, which showed the histological features of GO, was successfully established using the Cre-loxP system. This animal model offers improved insights and contributes to advancing methodological developments for GD and GO.