Heritage objects are continually at risk from the harmful agents of deterioration, and these risks may be exacerbated by climate change [2]. Therefore, heritage institutions need to adopt a position of climate resilience; they must “anticipate, absorb, and adapt” to the effects of climate change to preserve cultural heritage for future generations [10]. One crucial step is to understand how the future climate may affect the environments surrounding heritage objects whether they are on display or in storage. Every museum and its collection is unique, so most recent research has focused on climate change case studies for particular heritage sites [9]. The next challenge is to forecast the environmental conditions and associated risks to heritage objects at a broader scale. Machine learning and data science have the potential to make this analysis accessible for more heritage institutions.