Convolutional networks for statistical post-processing of wind gusts predictions. The wind gusts can be defined as a brief increase of the average wind speed, for usually less than 20 seconds. These sudden bursts in the wind speed are critical because they can cause different types of damages. Our research project focuses on the estimation of the conditional probability P(Y |X), where X are the prediction for different types of weather variables, while Y are the wind gusts speed real observations. To take advantage of the spatial patterns, existing in our input data (we are working with gridded predictions from the Harmonie model), we decide to use different techniques based on convolutional architectures.