Leaf wetness duration (LWD) is recognized as a very important conditioner of crops and forests diseases, but clearly, there is a considerable gap in literature on temporal models for prediction of LWD in broad regions from standard meteorological data. The objective of this study was to develop monthly LWD models based on the relationship between hours of relative humidity (RH) ≥ 90 % and average RH for Brazil and based on these models to characterize the temporal and spatial LWD variability across the country. Two different relative humidity databases, being one in an hourly basis (RH_h) and another in a monthly basis (RH_m), were used. To elaborate the LWD models, 58 automatic weather stations distributed across the country were selected. Monthly LWD maps for the entire country were prepared, and for that, the RH_m from the 358 conventional weather stations were interpolated using geostatistical techniques. RH_m and LWD showed sigmoidal relationship with determination coefficient above 0.84 and were highly significant (p < 0.0001). In relation to the validation of the LWD monthly models, a very good performance for all months was obtained, with very high precision with r between 0.92 and 0.96. Regarding the errors, mean error showed a slight tendency of overestimation during February (0.29 h day⁻¹), May (0.31 h day⁻¹), July (0.14 h day⁻¹), and August (0.34 h day⁻¹), whereas for the other months, the tendency was of underestimation like January (−0.27 h day⁻¹) and March (−0.25 h day⁻¹). Even as a first approach, the results presented here represent a great advance in the climatology of LWD for Brazil and will allow the development of studies related to crop and forest diseases control plans.