This thesis examined the use of Geographic Information Systems (GIS) software for predicting areas at risk of future stone decay on the Second Bank. By analyzing correlations between stone conditions, characteristics, and locational situation it was possible to determine statistical relationships between these variables. By understanding these relationships through the lens of known mechanisms of stone decay it was then possible to predict which stones are at greatest risk of developing future decay. This process is valuable because it can highlight enabling factors for stone decay and relationships between the complex variables on a building's surface that may not be visible upon casual observation. The end result provided a way to determine which stones are potenially in danger and allowed for targeted preventative treatments to be employed.