The objective of this paper is to quantify the use of past seismicity to forecast the locations of future large earthquakes and introduce optimization methods for the model parameters. To achieve this the binary forecast approach is used where the surface of the Earth is divided into l° × l° cells. The cumulative Benioff strain of m ≥ m c earthquakes that occurred during the training period, ΔT tr, is used to retrospectively forecast the locations of large target earthquakes with magnitudes ≥m T during the forecast period, ΔT for. The success of a forecast is measured in terms of hit rates (fraction of earthquakes forecast) and false alarm rates (fraction of alarms that do not forecast earthquakes). This binary forecast approach is quantified using a receiver operating characteristic diagram and an error diagram. An optimal forecast can be obtained by taking the maximum value of Pierce’s skill score.