This study presents a novel method to examine particle burnout in coal-fired utility boilers by extracting information from computational fluid dynamics (CFD) model results. The direct targeting of underlying causes enabled by this method can provide dramatic improvement in the unburned carbon in fly ash (carbon-in-ash or CIA), improving the commercial value of the ash as an additive in the production of concrete and cement and improving boiler efficiency. Data for thousands of particles are extracted and summarized for engineering characteristics such as injection burner, particle size, residence time, and exposure to oxygen. As an example of the method, unburned carbon is studied for a 200MWe tangentially-fired utility boiler with CIA issues. The analysis, which is consistent with boiler operation data, reveals that a majority of CIA can be contributed by a disproportionately small number of sources, hence the advantage of a targeted approach. The analysis of the 200 MW boiler reveals that fewer than half of the burners contribute about 80% of the CIA and the two largest coal particle size classes contribute 70% of the CIA. Most importantly, however, the oxygen availability for the coal particles is found to be the key factor for coal burnout. Based on this result, a simple and targeted strategy to improve burnout by improving oxygen availability is designed. This method is predicted by the model to reduce CIA from 3.27% to 1.3% and NOx from 588 ppm to 503 ppm.