Is it possible to improve motion tracking accuracy and reliability by changing the tracking method depending on the environment? In motion tracking, the techniques to find a target in each environment have been increasing in parallel to the technology used to accomplish this task. With each of them improving, there are still some that are better than others, when taking into consideration the goal and the environment. This paper aims to create a framework that can help with the selection process to find out which motion tracking method fits better depending on the environment, its conditions and the target. This study uses data from other research, papers and articles, considering the environment in which it was tested and its conditions, as well as the overall capability of the method in question when introduced with different variables and in different scenarios. Categorizing motion tracking methods and understanding their capabilities in various scenarios provides many benefits in optimizing the selection and application of the same. The framework not only simplifies the selection process but also improves accuracy and adaptability. Ultimately, this approach leads to more efficient, reliable, and specific motion tracking solutions for each need.