CONTEXT: Most crop models are designed for point-based modeling and to simulate agronomic variables on their native spatial footprint, i.e. typically as a uniform field-scale value. Precision agriculture needs crop model simulations at sub-field scales to support differential management application. Spatialization processes are used to change the simulation scale of crop models. OBJECTIVE: The objective of this study is to investigate the spatialization of a complex crop model by using a spatial calibration approach to modify its native spatial footprint and to evaluate if it is relevant to use this kind of crop model at the within-field scale. METHODS: APSIM was spatialized to simulate durum wheat yield at different spatial scales (field, within-field and site-scale) on an experimental field under Mediterranean conditions in southern Italy. Ancillary soil data were used to derive potential management (modeling) zones at different scales, which were then used to spatially calibrate soil and biomass parameters in APSIM to spatially predict yield in two different production years (one year was used for calibration and the other for evaluation). Spatialized crop model performances were evaluated using the spatial balanced accuracy (SBA) score, a metric to evaluate the global preservation of patterns between maps.