Simple telematics devices known as OBD “dongles” are being used for a wide range of applications, including driver insurance programs, boundary and speed alerts for young drivers, and powertrain diagnostics. SGS has explored the potential for another application, using OBD dongle data to predict fuel consumption and tailpipe exhaust emissions. In this study, SGS accurately measured instantaneous fuel consumption and emissions in the laboratory and on the road using PEMS technology. We then employed an advanced analytical technique known as “machine learning” to discover the relationship between engine sensor data and exhaust emissions. The machine learning approach showed promise to predict fuel consumption and emissions more accurately, and could be used to augment government Remote OBD and emissions inventory modeling programs.