Cross-product terms in regression analysis refer to interaction terms created by multiplying two or more predictor variables, allowing the model to capture the combined effect of these variables on the response variable. This technique is particularly useful when the relationship between predictors and the response is not purely additive and can enhance the model's explanatory power by accounting for the interplay between predictors.