Accurate cost estimation is key to successfully competing in the international freight forwarding industry. Traditionally, this function been performed manually by skilled employees. However, the modern availability of powerful and affordable computers, coupled with recent advances in predictive analytics, offer the possibility of an automated method. This book offers a computer based technique for freight forwarding cost estimation based on a variation of the k-Nearest Neighbors (k-NN) data mining algorithm. The method was tested against seven years of shipping records from an actual freight forwarding firm in Ireland. The results of this study would be of interest supply chain researchers, data scientists, and developers of cost estimating software.