Bayesian Networks are used to model a user's behaviour. There is not much research on the use of Frequentist Inference to accomplish this same task. This paper aims to analyze and describe the differences between inference methods: Bayesian and Frequentist. A simulation was conducted using Conditional Probabilities that were drawn from the Drupal Usability Study that was conducted in 2012 to apply to both inference methods, Bayesian and Frequentist. Results from this simulation showed that for most probabilities, Bayesian and Frequentist values are reasonably close. Although more frequentist values were equal to 50% than Bayesian values. With this, it was deduced that for Adaptive User Interfaces, Bayesian Inference is a superior method to use.