Graphite composite insulation boards (GCIB) have emerged as a promising solution in the construction industry, offering a combination of fire resistance, high temperature stability, and excellent insulation properties. As their usage continues to increase, it is crucial to develop and validate a more accurate theoretical model for the effective design and optimization of building insulation systems. Traditional models including series and parallel models are employed for estimating the thermal conductivity of GCIB but revealed higher relative errors and lower theoretical calculation accuracy. Therefore, the primary objective is to design and validate a more efficient theoretical model for thermal conductivity prediction in GCIB. This paper investigates the thermal conductivity of GCIB under varying composition ratios by designing a novel Parallel-Series Parallel (PSP) approach. The PSP model is designed based on a single basic cell where the graphite polystyrene particles are employed as the matrix material while cement, vitrified microspheres, and silica fume are used as inclusion materials. Then, the thermal conductivity unit is divided into three parallel heat conduction subunits where the matrix materials and inclusion materials in the three subunits are integrated in a series-parallel manner to provide a more realistic representation of the heat transfer mechanisms within the composite. For a comprehensive assessment, the study encompasses theoretical analysis, empirical assessment, and finite element (FE) simulations to illustrate its thermal properties. The predicted thermal conductivity reveals perfect consensus in comparison with the FE and experimental test outcomes by achieving lower relative errors of 2.7 %∼3.8 % and 1.9 %∼ 3.0 % respectively. The model validated through numerical simulations and sample experiments illustrates a significant improvement in accuracy of about 76.4 %∼94.3 % when compared to traditional series and parallel methods. Prominently, the findings indicate that the thermal conductivity of GCIBs declines considerably as the volumetric ratio of graphite polystyrene particles (Ф1/Ф3) increases and stabilizes when the proportion reaches 10, emphasizing the importance of optimizing material composition to enhance the thermal performance of GCIB. Overall, the validated PSP model by accurately determining the thermal conductivity of GCIB serves as a reliable tool for designing and optimizing high-performance insulation materials, contributing to energy efficiency and sustainability in building and construction industries.