Over the last several decades, the overall air quality goal in the United States has been to protect public health and clear skies by reducing emissions. At the same time, however, the risk of catastrophic fire has been rising in forests around the country as overly dense trees and understory brush crowd the stands. Prescribed fire-planned, controlled burning within specified conditions-is one important tool used to reduce hazardous fuels in forests, woodlands, and grasslands. Land managers are faced with the challenge of reducing fire risk while meeting air quality standards. Effective smoke management for prescribed burning requires reliable forecasting of potential smoke effects. Although forest fire managers have long known the basics of smoke movement, it is far more difficult to predict how much particulate matter and emissions will be produced, what the smoke will do a long way from the source, what the smoke will do the next day, and what the cumulative effects of smoke from multiple prescribed fires or wildfires will be. Scientists from the USDA Forest Service Pacific Northwest (PNW) Research Station, along with many partners, have developed the BlueSky framework to meet these management needs for accurate smoke forecasting. Started as a regional project in the Pacific Northwest, BlueSky has been expanded to provide real-time predictions from large wildfires throughout the contiguous United States and from prescribed fires in some regions. BlueSky is a framework that contains and combines models and data about weather, fires and fuels, emissions, and terrain. By integrating these models into a unified framework, BlueSky is able to predict smoke concentrations and trajectories, and can be used to create forecasts helpful to land and fire managers. The story continues inside of what has been accomplished so far in smoke forecasting.