Engineering critical components, such as turbine disks, blades, and reactor pressure vessels, are widely used in major equipment. The structural integrity of these critical components is the primary focus of ensuring safety of major equipment, which requires to be assured throughout the entire operating life. Due to unexpected aging effects, mechanical properties of critical components often require safety consideration related to the mechanisms involved in aging, including multi-physics failure mechanisms, such as fatigue, creep, corrosion, and thermal aging. 1,2 As the next generation of major equipment, such as aircraft engine, steam turbine, and nuclear reactors, should work under extreme harsh conditions, continued improvements in reliability assessment and life prediction of critical components have been possible through the accurate modeling of multi-physics failure mechanisms and the introduction of advanced processing approaches. [3][4][5] Based on physics-of-failure (PoF) modeling, their performance degradation assessment, system reliability modeling, and life estimation should be conducted to maximize lifetime and optimize inspection and maintenance policy of critical components. Moreover, failure occurs under influence of diverse uncertainties, including load variations in usage, material properties, geometry variations within tolerances, and other uncontrolled variations. 6,7 Thus, probabilistic methods and tools are required to account for these uncertainties. In recent years, a large number of advanced analytical, computational, and experimental techniques have been developed. Some examples can be found in the study of Jiang et al. 8 and Cang et al., 9 which greatly contribute to the exploration of PoF-based methods for reliability and life prediction of critical components.The purpose of this special collection is to provide an opportunity for researchers working in academy or industry to show their latest theoretical, numerical, and experimental aspects of structural life and reliability assessment and field applications of critical components; more recent progress can be found in the study of Yan et al., 1 Zhu et al., 4 Tahir et al., 5 Jiang et al., 8 Wang et al., 10 and Huang et al. 11 This special collection contains 23 contributions of authors coming from seven