［Objective/Significance］The complex interfacial microstructure is the weakest link in the coating-substrate system，and the interfacial fracture toughness is a key indicator for the evaluation of the coating's ability to resist the initiation and propagation of interfacial cracks. Accurately assessingthe interfacial fracture toughness is not only a core basis for determining interface failure analysis butalso a prerequisite for achieving the optimal design of coatings with high strength and high toughness.［Analysis/Discussion/Progress］Currently，the evaluation methods for interfacial fracture toughness are complex and diverse，mainly divided into two categories：load-based methods and energy-based methods. Energy-based methods，starting from the perspective of the global energy balance of the system，provide a fracture driving force indicator with clearer physical meaning and greater stability.This paper primarily introduces evaluation methods for interfacial fracture toughness based on theenergy method. First，the advantages of the energy method for evaluating interfacial fracture toughness are outlined. Second，the principles，development status，application scenarios，advantages，and disadvantages of seven energy-based evaluation methods for interfacial fracture toughness are exemplified，including the tensile test method，blister test method，bending test method，cantilever beam test method，indentation test method，scratch test method，and finite element analysis. Subsequently，the application of machine learning in the intelligent design of coatings is analyzed.［Conclusion/Prospect］Despite the development of various methods for evaluating interfacial fracture toughness，a universal testing technique remains unavailable. Due to discrepancies between idealizedexperimental conditions and actual failure behavior，each method has its limitations，underscoring theneed for technological innovation and multi-method collaboration to enhance applicability. Future research should integrate interfacial fracture mechanics with materials science，combine diverse testing techniques with machine learning，and enable accurate prediction of interfacial fracture behavior， thereby advancing coating technology toward digitalization and intelligence.