In the field of bridge Structural Health Monitoring, the possibility of an efficient damage detection is affected by confounding influences due to operational and environmental variability. In static monitoring of a bridge, not only temperature, but also other factors such as traffic loads, wind and friction, can have a big influence on the observed data. It is therefore necessary to understand in first place what constitutes a normal response to environmental and operational loadings, allowing to filter those effects and correctly identify anomalous behaviour. The primary objective of this thesis is to develop a predictive model that can filter the normal structural responses to environmental loads, establishing a baseline that highlights only those displacements caused by structural anomalies.