Precise spatiotemporal dynamics of Rho GTPases are essential for efficient cell migration. Manipulating Rac1 and RhoA signaling is thus a potential intervention strategy to abrogate harmful cell invasion and subsequent metastasis; however GTPase signaling can be extremely complicated due to crosstalk and the multitude of upstream regulators and downstream effectors. Studying Rho GTPase networks in a formal mathematical setting can therefore be of great use. We recently built a predictive model based on Boolean logic which identified a negative feedback loop critical for RhoA and Rac1 activity. Here, we discuss the value and potential pitfalls of different mathematical approaches which have been used to study Rho GTPase dynamics, and highlight the importance of choosing the correct approach given the data available and outputs desired. Overall, a mathematical approach, particularly when combined iteratively with in vitro experiments, can be of great use in deriving new biological insight to further harness the activity of Rho GTPases.