A new method was developed to predict the distribution of response values based on covariates. This method, called regression copula, combines a copula model with a nonparametric margin to create smooth predictions. The copula is estimated using Hamiltonian Monte Carlo and variational Bayes, which is scalable to high dimensions. By applying this method to real data on electricity spot prices, the researchers found that the predictions were more accurate compared to other models.