Product tolerancing decisions made in product design have a significant effect on manufacturing environmental and cost performances by strongly influencing both the selection and operation of processing machinery. These decisions however are typically made without quantitative knowledge of their effects in manufacturing. With estimates of environmental and cost performances of manufacturing processes required to achieve specific part designs earlier in the product design cycle, designers may make more informed, and potentially better, design decisions with respect to manufacturing environmental and cost performance goals. In this thesis a method for quantifiably relating product tolerancing decisions to environmental and cost performances in manufacturing in order to provide decision support for cost and environmentally conscious design for manufacturing is developed. The method is instantiated as an Excel-based tool and exercised by two illustrative examples of increasing complexity, as well as a study of the manufacture of automotive transmission pinion gears with differing tolerance requirements. Uncertainty analysis is performed through the use of @RISK software; the uncertainty of parameters associated with manufacturing operations and machinery is captured through the use of probability density functions and Monte Carlo simulation is performed. Simulation results provide insight into the uncertainty of performance estimates and the risks associated with ensuing decision making. This method may be useful to product designers, as well as process planners, to support decision making efforts related to cost and environmental consciousness in the manufacturing phase of the product life cycle.