This work focuses on the spatial and temporal variability of burnt area (BA) in the entire Iberian Peninsula (IP) and on the construction of statistical models to reproduce the inter-annual variability. A novel common dataset was assembled for the whole IP by merging the registered BA from 66 administrative regions of both Portugal and Spain. We applied a cluster analysis to identify larger regions with similar fire regimes and results point to the existence of four clusters (Northwestern, Northern, Southwestern and Eastern) whose spatial patterns and seasonal fire regimes are shown to be related with constraining factors such as topography, vegetation cover and climate conditions. The relationship between BA at monthly time scale with both long-term climatic pre-conditions and short-term synoptic forcing was assessed using correlation and regression analysis based on: (1) temperature and precipitation from 2 to 7 months in advance to fire peak season, (2) synoptic weather patterns derived from 11 distinct Weather Types Classifications (WTC). Different relations were obtained for each IP region with a relevant link being identified between BA and short-term synoptic forcing for all clusters, while the relation with long-term climatic preconditioning was relevant for all but one cluster. Stepwise regression models based on the best climatic and synoptic circulation predictors were developed with cross-validation to avoid over fitting. The performance of the models varies within IP regions, though models exclusively based on WTC tend to better reproduce the annual BA time series than those merely based on pre-conditioning climatic information. Nevertheless, the use of both synoptic and climatic predictors provides the best results, particularly for the two western clusters, with Pearson correlation coefficient values higher than 0.7. Finally, it is shown that typical synoptic configurations that favour high values of BA correspond to dry and warm wind flows associated with anti-cyclonic regimes.