Airspace capacity estimates are important both for airspace design and for operational air traffic management. Considerable effort has gone into understanding the complexity factors that reduce sector capacity by increasing controller workload. Yet no analytical means is available for accurately estimating the maximum capacity of an en route sector. The Monitor Alert Parameter (MAP) values that determine the operational traffic limit of en route sectors in the United States account only for workload from inter-sector coordination tasks. We propose a more complete sector capacity model that also accounts for workload from conflict avoidance and recurring tasks. We use mean closing speeds and airspace separation standards to estimate aircraft conflict rates. We estimate the mean controller service times for all three task types by fitting the model against observed peak traffic counts for hundreds of en route airspace volumes in the Northeastern United States. This macroscopic approach provides numerical capacity predictions that closely bound peak observed traffic densities for those airspace volumes. This paper reviews recent efforts to improve the accuracy of the bound by replacing certain global parameters with measured data from individual sectors. It also compares the model capacity with MAP values for sectors in the New York Center. It concludes by illustrating the use of the model to predict the capacity benefits of proposed technological and operational improvements to the air traffic management system.