Tobacco budworms and aphids are the major pests in tobacco-growing areas of Vietnam. Aphids do not only cause direct damage but also transmit many viruses, such as potato virus Y, Cucumber mosaic virus, etc. To effectively prevent pests and diseases, contributing to reduce damage caused by insect pests and the use of pesticides, in recent years, the tobacco institute has built a combined predictive model between Skybit models, Fuzzy and Degree days that is run on the Excel software. Based on the interaction between the pest, environmental conditions (temperature, humidity, rainfall), and the development stage of tobacco gives forecast results and advises the best controls. Through the study results show that the accuracy of forecast the tobacco budworms and aphids is from 83% to nearly 100%. For the aphids, the model that combines between the Skybit and Fuzzy has the most accurate predictive effect. Forecast the aphids by the Degree Days model is low predictive efficiency and can not apply in forecast the tobacco aphids. With tobacco budworms, forecast model that combines between Skybit models, Fuzzy and Degree days gives the highest predictive results. The predictive model is more accurate when the the weather factors little change. Based on the predictive and observable results, we give the best control methods that reduce the damage caused of insect pests; reduce the use of pesticides compared to years ago; increase yield and quality; and increase income for tobacco-growing farmers