The Pairwise Comparison technique is a general purpose estimation approach for capturing expert judgment. This approach can be generalized to a probabilistic version using Monte Carlo methods to produce estimates of size distributions. The probabilistic pairwise comparison technique enables the estimator to systematically incorporate both estimation uncertainty as well as any uncertainty that arises from using multiple historical analogies as reference modules. In addition to describing the methodology, the results of the case study are also included. This paper is an extension of the work presented in [Estimation of Software Size and Effort Distributions Using Paired Ratio Comparison Matrices] and will show how the original software size estimates compared to the actual delivery size. It will also describe the techniques used to modify the approach based on lessons learned. The results because they are based on only one case do not validate the effectiveness of the proposed approach but are suggestive that the technique can be effective and support the conclusion that further research is worth pursuing.