Estimating energy flows that affect temperature increases inside houses is crucial for optimizing building design and enhancing the comfort of living spaces. In this study, a thermal model has been developed to estimate the internal temperature of rural houses in Mexico using aerial thermography. The methodology used in this study considered three stages: (a) generating a semi-experimental thermal model of heat transfer through roofs for houses with high infiltration, (b) validating the model using contact thermometers in rural community houses, and (c) integrating the developed model using aerial thermography and Python 3.11.4 into user-friendly software. The results demonstrate that the thermal model is effective, as it was tested on two rural house configurations and achieved an error margin of less than 10% when predicting both maximum and minimum temperatures compared to actual measurements. The model consistently estimates the internal house temperatures using aerial thermography by measuring the roof temperatures. Experimental comparisons of internal temperatures in houses with concrete and asbestos roofs and the model’s projections showed deviations of less than 3 °C. The developed software for this purpose relies solely on the fundamental thermal properties of the roofing materials, along with the maximum roof temperature and ambient temperature, making it both efficient and user-friendly for rural community management systems. Additionally, the model identified areas with comfortable temperatures within different sections of a rural community, demonstrating its effectiveness when integrated with aerial thermography. These findings suggest the potential to estimate comfortable temperature ranges in both rural and urban dwellings, while also encouraging the development of public policies aimed at improving rural housing.