This research is aimed to evaluate risk factor on Fama-French 3 factors model associated with market risk, business size, and value premium which affected the returns on three industry group in the stock exchange of Thailand-Agro and Food, Services, and Technology. Methods of Markov-Switching Seemingly Unrelated Regression and Copula were used I the model to estimate beta coefficient due to an interesting perception of marginal distribution from simultaneous equations system could be linked together no matter if they were symmetry or asymmetry related and to create different regimes of the marketing changing effects of coefficient values. We estimated the model in different copula families with marginal probabilities and choose the best model which produced the smallest Akaike’s Information Criterion (AIC) and Bayesian Information Criterion(BIC) values. Finally, the result showed that estimated betas significantly represented coefficients of the market risk, Business size, and value premium had effects to the returns on all three industries. According to high significant coefficients estimated by MS-SUR copula with the model, we concluded that using method had the ability to capture the effects of variables in the model and be able to explain important market events through the period of the study. Moreover, less than one of beta coefficients on market risk for both bullish and bearish market would take the rate of change in returns on the industries smaller than the rate of change in total market returns.