The thermal analysis of small satellites (SmallSats) is often given a low priority compared to other sub-systems, due to the short timelines and small budgets associated with SmallSats. However, the satellite's temperature is crucial for preventing mission failures. In this thesis, a new, open-source, modular software for thermal analysis of SmallSats is created with the Python coding language, to simplify and speed up the thermal analysis process. This modularity is achieved by: ensuring that any thermal model can be connected to any other thermal model with a single connect function, allowing a hierarchical model structure that is easily mutable and re-usable; integrating a material database into the software, allowing frequent re-use of common materials, coatings, and contact connections; and including a dedicated sensitivity analysis tool in the software to allow the user to assess the sensitivity of the model's temperatures on various input parameters. To assess the quality of the software's computations, they were verified with the commercial ESATAN-TMS software, and validated with flight data from the FUNcube-1 CubeSat. The validation showed Root-Mean-Square Errors ranging from 1.4 degrees C to 7.1 degrees C for the outside panels of the satellite. With a sensitivity analysis performed on FUNcube-1, it was found that the solar absorptivity of the spacecraft demonstrates the greatest influence on simulation outputs: the largest risk may be its degradation throughout time, due to ultra-violet and atomic oxygen exposure. If the satellite would have had white paint, a year-long degradation could lead to a 17.1 degrees C temperature increase of the maximum achieved temperature in the satellite, depending on the type of paint used. Further development into this software should aim to validate the model even further with different satellites, which will be an important step towards making this tool a standard for SmallSat thermal analysis.