This work introduces a methodology to evaluate, rank, and select suppliers for an organisation managing a large and complex construction project. The company's procedure to complete a supplier evaluation is conflated with other supplier features such as product type and complexity, delivery characteristics and requirements, and geographic location of the project. The introduced model segregates the effects of each feature and then aids supplier selection on various criteria without the confounding effects. Model parameters are determined using Bayesian estimators allowing for information integration from prior periods. The estimation approach provides rich model parameter data, allowing for use in additional analysis. This work advances the research in supplier selection by illustrating a practical forecasting and predictive technique for supplier selection. One result is that the separability of factors in a multiple criteria decision environment can prove valuable for managers to help decipher and isolate factors in a complex decision environment. The technique is feasible for smaller problem sets and provides a robust solution. Past performance and future performance potential are both considered. Analysis and future research directions allow for further development.