A computer-implemented training method for a machine learning model intended to carry out corrosion estimations about a vehicle, wherein at least one vehicle is equipped with at least one corrosion sensor, wherein the vehicle is provided with a contamination sensor configured to measure a conductance which is representative of a contamination of at least one surface of the vehicle, the method comprising: determining the location of the vehicle by means of a GPS device provided in the vehicle, determining, in a weather station database, which weather station is the closest to the location of the vehicle, retrieving at least some weather data from said closest weather station, retrieving at least some corrosion data from said at least one corrosion sensor, retrieving at least some contamination data from the contamination sensor, building a training database associating, for several moments over at least ten days, said corrosion data with said weather data, recording at least some contamination data in the training database for at least some moments of said several moments, and training the machine learning model on the training database thus built, wherein the weather data and the contamination data are used as input training data, and the corrosion data are used as target output training data. wherein at least one vehicle is equipped with at least one corrosion sensor, wherein the vehicle is provided with a contamination sensor configured to measure a conductance which is representative of a contamination of at least one surface of the vehicle, the method comprising: determining the location of the vehicle by means of a GPS device provided in the vehicle, determining, in a weather station database, which weather station is the closest to the location of the vehicle, retrieving at least some weather data from said closest weather station, retrieving at least some corrosion data from said at least one corrosion sensor, retrieving at least some contamination data from the contamination sensor, building a training database associating, for several moments over at least ten days, said corrosion data with said weather data, recording at least some contamination data in the training database for at least some moments of said several moments, and training the machine learning model on the training database thus built, wherein the weather data and the contamination data are used as input training data, and the corrosion data are used as target output training data. determining the location of the vehicle by means of a GPS device provided in the vehicle, determining, in a weather station database, which weather station is the closest to the location of the vehicle, retrieving at least some weather data from said closest weather station, retrieving at least some corrosion data from said at least one corrosion sensor, retrieving at least some contamination data from the contamination sensor, building a training database associating, for several moments over at least ten days, said corrosion data with said weather data, recording at least some contamination data in the training database for at least some moments of said several moments, and training the machine learning model on the training database thus built, wherein the weather data and the contamination data are used as input training data, and the corrosion data are used as target output training data.