Newsboy problem has always been an important issue in inventory management. A number of methods have been proposed to solve such problems based on different objectives or considerations. Traditional newsboy models assume full knowledge of the demand probability distribution; however, in reality, it is often difficult to completely characterize the demand. Therefore, many researchers focused on the newsboy problem with partial (or limited) information. This paper constructs an online riskreward model for the newsboy problem with rang information under probabilistic forecasts. Using the above method, this paper designs the risk tolerance strategy and proves its competitive ratio to help the newsboy choosing the optimal strategy according to his own risk tolerance and probabilistic forecast.