Rural buildings comprise about 60% of India’s national building stock. These buildings are naturally ventilated, carrying an inherent resilience to passively regulate indoor comfort in response to external climatic conditions. They also exhibit a greater resilience to withstand climate change when compared with dwellings adopting modern building materials. The performance of a building is typically examined based on indoor parameters such as temperature, humidity, air velocity, and air quality. So far, the building performance predominantly relied on temperature. There is an increasing realisation and awareness of the concerns of rising moisture levels causing physiology. Parameters are affected by building properties such as orientation, envelope design, window-to-wall ratio, aspect ratio, and many more in response to outdoor climatic conditions. With climate change happening, response of building varies and there is a need to assess for the inertia (resilience) of the buildings to meet the requirements of the occupant’s comfort. The current study attempts to develop a framework for evaluating resilience using temperature and humidity in addition to relying on real-time data and simulation models, the methodology also tests a data science methodology to examine the influence of building elements on resilience. Two building typologies, vernacular and conventional, in the village of Suggenahalli, have been studied. A Synergistic Analytical Framework was developed using the Apriori algorithm, using the concept of Association Rule Mining, and tested for existing building physics relations. The results thus show the influence of building elements on heat index. It was found that vernacular dwelling’s resilience is affected by the low Air changes per hour, whereas in the conventional dwelling, it is the surface temperatures of roof.