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This paper presents a procedure for location-based forecasting of the potential vehicular charging load at off-home charging stations. A location-specific fuzzy decision making system is proposed to characterize the charging behavior and determine the probability of charging by means of a three dimensional input obtained from a real-world driving dataset. The obtained charging and parking probability figures are then used in prediction of the local aggregated charging demand. The flexibility and usefulness of the developed procedure is exemplified in the case studies of two major shopping centers.