Over four years, the InSight mission has recorded more than 1,300 marsquakes. As on Earth, these marsquakes follow the Gutenberg-Richter law, which describes the frequency of quakes in relation to their magnitude. In this study, we focus on the b-value, which characterizes the frequency of smaller events relative to larger ones. On Mars, however, only one station has been settled. Hence, although very sensitive, the mars quake catalog is incomplete, even at sufficiently large magnitude. Consequently, detectability of the events must be carefully considered. We parameterize a detection function that depends not only on the event magnitude but also on the epicentral distance to the Insight station. Several factors, such as the use of a single station, significant seismic noise, and the high diffusivity of seismic waves on Mars, have made it challenging to assign a magnitude and epicentral distance to all recorded events. Only 52 low-frequency (LF) and 151 high-frequency (HF) events have both known epicentral distances and magnitudes. Therefore, to determine the b-value, it is necessary to use a method that accounts for detection to leverage the full available dataset. We propose to conduct a Bayesian analysis with a Markov Chain Monte Carlo (MCMC) algorithm on the Martian catalog using this detection function in order to properly estimate the b-value and its uncertainty. A similar analysis will then be carried out on the Moon using seismic data from the Apollo missions and the upcoming FSS mission, with the aim of linking observed seismicity on one-plate planet and the build-up of stress through lithosphere cooling.