On the methodological aspect, the case study established that the statistical models usually encountered in the literature related to statistical cost modelling—namely MLR and ANNs—are superseded in terms of performance by more recent techniques from the fields of Data Mining and Machine Learning, notably Support Vector Regression and Gradient Boosted Trees. It also appears that the various statistical techniques yield complementary perspectives on the cost data and should thus be used concurrently. Moreover, ensemble methods may be a worthwhile solution to optimally average the cost estimates from several models. The analysis also generated valuable engineering insights. First of all, MLR showed that the cost of material accounts for a small portion of total manufacturing cost.