The probability of failure of engineering systems is typically time variant due to the effects of environmental conditions and operational loads. Such effects affect the system properties (state variables) that define the system ability to sustain future demands and the demands they might be facing. Therefore, it is of primary importance to estimate values of the state variables over time. Structural Health Monitoring (SHM) and Non-Destructive Evaluation (NDE) can be used in estimating the state variables at different times. However, typically this identification process is an ill-defined problem, i.e. different combination of the state variables can be possible to achieve the same values from SHM or NDE. Also SHM and NDE values cannot be used directly to obtain estimates of the probability of failure of the system at future times. To address these issues, this paper couples SHM and NDE with physics-based probabilistic models of the state variables that capture the physics of the deterioration process. The models can be calibrated using SHM and NDE data in a well-defined problem and can be used to estimate the values of the state variables at future times.