The estimation of TSR intensity plays a crucial role in the design and performance optimization of solar energy systems, as it can vary significantly depending on geographical location and climatic conditions. Various transposition models can be applied to estimate TSR on tilted and tracking PV surfaces. In this study, the Liu-Jordan isotropic and the Perez anisotropic models were applied to provinces in Türkiye’s Central Anatolia region to provide more reliable predictions of annual solar energy yields. This study conducts a comparative analysis to highlight the significant output fluctuations and discrepancies between the two proposed models. The findings indicate that PV energy production in Central Anatolia can be greatly improved with the proper installation of an STS. The annual optimal tilt angle (OPTA) was estimated to be between 29° and 30° utilizing the Liu-Jordan model, while the Perez model suggested an OPTA range of 33° to 35°. It was determined that the anisotropic components in the Perez model predict optimal angles that are 3°–4° higher than those estimated by the Liu-Jordan model. The average OPTA for the Central Anatolia region was found to be 30° according to the Liu-Jordan model and 34° according to the Perez model. The Perez model also indicates that by slightly increasing the tilt angle, more TSR can be captured, particularly during the winter months. According to this study, certain solar characteristics incorporated into anisotropic models improve the precision of the estimated outcomes. The differences in TSR intensity predictions between the Liu-Jordan isotropic and Perez anisotropic transposition models were determined as 4.78% for fixed systems, 8.55% for single-axis STS, and 10.01% for dual-axis STS on average. The proposed models can be employed to precisely predict TSR intensities on tilted and tracking PV surfaces for a range of geolocations in Türkiye and worldwide.