Heavy-duty diesel maintenance equipment consumes significant amounts of fuel and consequently emits substantial quantities of pollutants. The purpose of this study was to identify which engine activity variables had the greatest impact on fuel use and emissions rates. A real-world data set was used for a case study fleet containing backhoes, motor graders, and wheel loaders. Multiple linear regression was used to assess the relationships between engine activity variables and fuel use and emissions rates. The engine activity variables of engine speed, manifold absolute pressure, and intake air temperature were used to predict mass per time fuel use and emissions rates of nitrogen oxides, hydrocarbons, carbon monoxide, carbon dioxide, and particulate matter. The results indicated that manifold absolute pressure had the greatest impact on fuel use and emissions rate predictions. Based on this finding, fuel use and emissions estimating models based on manifold absolute pressure were developed as a practical estimating tool for practitioners.