The first year effort was devoted to determining the lifting capacity of the industrial population, both males and females. In addition, based on the data collected, a set of predictive models for the lifting capacity in the sagittal plane will be developed using both operator and task variables. The operator variables include: 1) strength measures, 2) anthropometric measures, 3) endurance measures, and age. Task variables include: box size, lifting frequency, and lifting range (starting and ending points). The second year effort will make use of these models to study, utilizing a separate sample set of operator sample in the cooperating industries, to determine the likelihood of injury as related to job severity. Once the predictive models are developed they will be used to predict medical incidence in industry (medical incidence defined as employee time lost in man-hours per year due to manual materials handling tasks). This is performed by deriving the Job Severity Index (JSI) where JSI equals (Task demands (weight, bulk, freq., range) over (Max, accept. wt. of lift from predictive models). The higher the JSI, the more a worker is approaching his/her own max. acceptable weight of lift. For a given (JSI), then the question becomes; what is the likelihood of a medical incidence? Actual field data on JSI and medical incidence will be gathered from the participating plants. From this data regression methods will be used to develop relationships between JSI and medical incidence. Of particular interest will be the development of the lower 50, 75, 90, 95, and 99 confidence interval estimates on expected medical incidence. A typical (hypothetical) result will be: Probability (expected medical incidence greater than 16 man hours, given that JSI equals 0.7) equals .75.