Abstract: A method of computing an estimated queuing delay is described that uses both historical queue delay data in the form of multiple calendar-based queue delay profiles and real-time data in the form of field-reports from service objects of actual queue delay. A decision selects either the source data from queue delay profiles or a real-time report. A clustering algorithm is used to assign potentially widely disparate geographic locations to clusters and to assign service type records to a cluster. Calendar-based queue delay profiles may be associated at the cluster level, at the service-type level, and at the individual service point level. Service objects may request an estimated queue delay; service objects may be provided with a estimated queue delay for a specified service point and also delays for alternative service points. Such requests may be prior to selecting or moving to a particular service queue.