The computation of normalizing constants often brings (higher-dimensional) integrals, which could not be computed analytically or are computationally expensive. Stochastic methods will be explored to find an estimate for normalizing constants. These stochastic methods will be used to estimate the Bayes factor. With this Bayes factor can be searched for a best fitting model to data.