In recent years, Bayesian Inference has become the standard framework for quantifying uncertainty in astronomical conclusions. In practice, methods such as Markov Chain Monte Carlo (MCMC) are commonly used to produce samples from the posterior distribution, making marginalization straightforward. However, MCMC typically cannot compute the normalizing constant needed for model selection, and often...