The invention discloses a user consumption behavior prediction model training method and device, equipment and a storage medium, and relates to the technical field of machine learning model training.The method includes: obtaining training set and a test set from a database; obtaining a prediction model initialization weight vector, an inverse connection function and a learning rate parameter; forany training data, normalizing the weight vector and constructing a first random variable, sampling the first random variable for multiple times to obtain a first inner product estimated value, and updating the weight vector according to the inverse connection function, the first inner product estimated value, the label information of the training data and the learning rate parameter; and testingeach weight vector by adopting test data, and obtaining a prediction model of the trained user consumption behavior according to the weight vector with the minimum risk of the prediction model. In the generalized linear model training process, inner product estimation is approximated by sampling random variables multiple times, the model training efficiency is improved, the model accuracy is ensured, and the generalized linear model can effectively predict user consumption behaviors.