During the long-term operation of aircraft engines, the aerodynamic performance of fan and compressor components tends to degrade over time, leading to increased fuel consumption and elevated environmental impact. This reduced performance is primarily caused by damage to the leading edge of the compressor and fan blades, as well as increases in surface roughness and blade tip clearances, which result from erosion and mechanical damage due to foreign objects entering the engine. Damage to the leading edges of compressor and fan blades is especially critical during operation at transonic speeds, where aerodynamic performance is highly sensitive to variations in leading edge geometry. Additionally, the deterioration of these components results in higher maintenance expenses and accessibility challenges for users. The objective of this research is to mitigate the adverse effects of blade damage and degradation through the development of experimental and modelling techniques that enable the identification of damage and erosion using the aerodynamic and aeromechanical response of the machine as an input. By enabling the online detection of damage and erosion through sensors and advanced algorithms, potential decreases in performance due to degradation may be prevented. This approach allows for the identification of required maintenance procedures in real-time without the need for visual inspections. This is particularly beneficial when limited access to components would otherwise require the complete disassembly of the engine during routine inspections and maintenance procedures. Moreover, repairing aero-engine components is critical for sustainability, as it may enable the recovery of lost performance due to damage and degradation, potentially preventing the need to replace blades or entire blisks. In addition to these challenges, there is a limited understanding of how damage and degradation impact the aeromechanical properties of compressor and fan blades, such as their forced response or flutter stability. Developing an understanding of these effects is therefore an additional core interest of the proposed project. To characterize the aerodynamic and aeromechanical performance of nominal and damaged compressor blisks under both subsonic and transonic conditions, experimental campaigns will be conducted, and a numerical high-fidelity modelling approach for damaged compressor blades will be developed, verified, and validated. Results from the experimental campaigns and numerical simulations for the nominal (undamaged) compressor blisk test object will serve as a baseline for evaluating the effect of damage and erosion on the aerodynamic and aeromechanical performance of axial compressors. After developing the numerical modelling approach, validating it against experimental results, and establishing an understanding of how damage and erosion affects the aerodynamic and aeromechanical performance of axial compressors, a machine learning model will be developed to predict the location and severity of erosion on the blades of axial compressors using corresponding input aerodynamic and aeromechanical data.