The increasing use of multi-layer composite materials in high-performance engineering applications has created a growing demand for accurate modeling of transient heat conduction. The heterogeneous and anisotropic nature of composite systems, combined with the presence of multiple material interfaces, introduces significant complexity in predicting time-dependent thermal behavior. This study presents a qualitative and systematic synthesis of existing research on transient heat conduction modeling in multi-layer composite materials with the objective of developing an integrated conceptual framework. A systematic literature review was conducted using major scientific databases, and the selected studies were analyzed using thematic analysis to identify dominant modeling approaches, key influencing parameters, and persistent research challenges. The findings reveal the predominance of numerical techniques, particularly finite element modeling, supported by analytical methods for theoretical validation. The analysis highlights the critical role of thermal interface resistance, anisotropic material behavior, and the increasing importance of multi-scale and multi-physics modeling. Emerging trends such as machine learning and digital twin technologies were identified as promising directions for improving predictive accuracy and reducing computational cost. The study identifies significant gaps in experimental validation, interface characterization, and integration of physics-based and data-driven approaches. Based on the synthesis, an integrated conceptual framework for transient heat conduction modeling is proposed. The findings contribute to a more unified understanding of thermal behavior in layered composite systems and provide guidance for future research in advanced thermal management and composite material design.