Materials adopted in civil, mechanical, automotive, naval, aerospace, and industrial engineering applications are rarely subjected to constant amplitude loading. While standard fatigue assessment is often based on simplified loading assumptions, the structural strength and durability under real-world service conditions, specifically variable amplitude and spectrum loading, remain a major concern in the design of engineering structures. In order to fully optimize design and ensure reliability, understanding and estimating the mechanical performance of materials and structures under complex, random, or block loading histories is of paramount importance. Therefore, the special session entitled “State of the art approaches for fatigue analysis of materials and structures subjected to variable amplitude and spectrum loading” will focus on state-of-the-art theoretical, numerical, and experimental approaches to investigate the fatigue behaviour of materials and structures under variable amplitude loading. Special attention will be dedicated to emerging technologies, specifically the application of Machine Learning (ML) algorithms for life prediction and Digital Twin frameworks for real-time structural health monitoring and prognosis.