Regression is a term typically used when predicting continuous output variables from continuous input variables.
The only difference between regression and classification is that we are typically dealing with continuous variables, and the mathematics behind the predictions is different.
This does not mean that there cannot be any discrete variables in the model.
An example of regression would be predicting a child's adult height, based on their current height and age.
The Bayesian network regression model shown below, demonstrates different design methods.