Abstract: The present disclosure relates to a method for classifying a non-monetary donation. The method comprises: training a machine learning model comprising input neurons arranged in an input layer, each input neuron being operable for inputting an input value (Xn) of a parameter of the donation, and at least one hidden layer comprising multiple hidden neurons, each hidden neuron being operable for calculating a hidden layer value based on at least one input value and weights (w(Xn, Ym)) associated with the respective input neurons. The number of input parameters may be reduced based on ranking the weights (w(Xn, Ym)) related to the individual input parameters. The number of neurons of the hidden layer may be reduced based on ranking the weights related to the individual neurons of the hidden layer. The trained model, the reduced input parameters, and reduced hidden neurons may be provided for enabling the classification using the trained model.