The impact of engineered products is a topic of increasing concern in society. The impact of a product can fall into the categories of economic, environmental, or social impact; the last category is defined as the effect of a product on the daily lives of people. Design teams lack sufficient tools to help improve the impact of products and understand the impact of products at scale in society. This dissertation aims to provide insight and methods for improving the social, environmental, and economic impact of engineered products. The majority of the research focuses on the prediction of product impacts on society, which requires a sociotechnical approach with models that contain aspects of the product and society. This begins with the introduction of an agent-based modeling approach to predict how changes to a design will ultimately impact society. Chapter 3 performs a systematic review of the literature to identify common challenges in product social impact modeling, identifies ways to mitigate the challenges, and provides a general process to create product impact models. Guidance on a general modeling process is essential to enable the widespread use of predictive impact models in engineering design. Chapter 4, provides guidance on creating sociotechnical models using primary survey data and machine learning for impact prediction using a case study of improved cookstoves in Uganda. Chapter 5 presents a method for incorporating environmental impacts, using life cycle assessment and agent-based modeling to properly scale impacts from the functional unit level to the societal level. A limitation of life cycle assessment in the early phases of product design is the difficulty of scaling impacts from the functional unit level to the population level. Using agent-based modeling together with life cycle assessment enables an understanding of the number of functional units required at the population level; allowing for the quantification of the total population-level impact. There are often trade-offs in the social, environmental, and economic sustainability space. To characterize these sustainability trade-offs, Chapter 6 illustrates the modeling of social, environmental, and economic impacts of a product and how to quantify the product sustainability trade-space. Chapter 7, presents work on identifying quantitative factors for selecting engineering global development project locations based on the potential for social impact. Finally, Chapter 8 provides the general contributions of this work, identifies limitations, and provides direction for future work. The research presented in this dissertation is a step toward a future where predictive modeling of the social, environmental, and economic impacts of products is commonplace in engineering design.