This article considers a regression model with coefficients that are specified by bodies of evidence defined on the numerical axis. Optimization problems of finding such evidential coefficients have been set. The relationship between the evidential formulation of the problem and some formulations of fuzzy regression problems is shown. The advantages of evidential regression compared to possibilistic fuzzy regression (better robustness, lower degree of fuzziness of coefficients) are demonstrated using a numerical example.