An automated Flight Condition Recognition (FCR) algorithm was developed and was used to identify helicopter flight conditions from recorded flight parameters. The algorithm was configured and validated for the Westland Lynx helicopter. The algorithm uniquely combines a conventional rule-based FCR approach with neural network identification of more challenging flight conditions. The algorithm was used to evaluate the effectiveness of FCR for fatigue management. A theoretical investigation was performed to analyse the effects of changes in an aircraft's operational environment on fatigue damage. The relationships established can be used to improve indirect methods of aircraft structural loads monitoring and to aid the management of aircraft fatigue damage. An approach was developed to synthesise aircraft weight and Centre of Gravity (CG) location from recorded flight parameters. The approach was successfully applied to the tandem rotor Boeing Chinook helicopter in a variety of steady flight conditions. Accurate synthesis of aircraft weight and CG location can be used to improve aircraft safety by identifying when aircraft are flown outside their operational limits. A current indirect structural health monitoring methods do not take account of dynamic effects such as rapid control movements, rotor faults, gusts, turbulence and landing. An approach was investigated for capturing the damaging effect of these dynamic rare events. The approach was successfully applied to both narrow band dynamic events such as rotor faults and broad band dynamic events such as hard landings.