In this paper, we investigate the rate of company compulsory liquidation (insolvency) (CCL) via Bayesian inference applied with the use of ‘OpenBUGS’ and ‘R’ software mediums. This study follows on from a previous ‘frequentist’ statistical based study of one of the authors and introduces the usefulness of Bayesian inference as the statistical tool. CCL occurs when a company creditor successfully petitions the courts for a winding up order. There are a finite number of variables that can affect the possibility of company creditors instigating CCL. The model in this study included those variables found to be statistically significant within the data range contained in the previous ‘frequentist’ study. We commence by presenting the model from the previous ‘frequentist’ study along with an analysis of the results of that study. We then introduce the concept of Bayesian inference to the study and apply the inference to the ‘frequentist’ model, and analyse the results of the new model. Finally, we then compare the two sets of findings and report our conclusions, and the implications for the modeling of insolvencies.