Material costs when cutting solid wood parts from hardwood lumber for secondary wood products manufacturing account for 20 to 50 percent of final product cost. These costs can be minimized by proper selection of the lumber quality used. The lumber quality selection problem is referred to as the least-cost lumber grade mix problem in the industry. The objective of this study was to create a least-cost optimization model using a design that incorporates a statistical approach to address shortcomings of existing models using linear optimization methods. The results of this study showed that optimal solutions tend to use as much low-quality lumber as possible to minimize costs. Comparison of results from this new least-cost grade mix model with other existing least-cost lumber grade mix models has shown that the new model results in lower-cost solutions.