This thesis investigates the accuracy of a model that the Department of the Navy uses to predict the financial health of major defense hardware contractors. The inputs to this model are six financial ratios derived from a firm’s income sheet and balance statement. The output of this model is a single Z-score that indicates the health of a firm. Depending on the score, a firm’s financial standing is classified as healthy, distressed, or uncertain. The model is tested using a database compiled for this thesis that includes financial information for a total of 72 defense and non-defense firms. The test database is unique relative to the underlying model database; it reflects a more recent timeframe and a greater number of firms, none of which were used to develop the model. Model accuracy was computed by measuring how often the model correctly classified a bankrupt firm as distressed and a nonbankrupt firm as healthy. Then, model accuracy was evaluated by comparing these test results (i.e., percent correctly classified) to results published by the model’s developers. This comparison produced mixed results. In light of this fact, the thesis concludes that the model should be improved and recommends a course of action. / Master of Arts