Tobacco blue mold is a serious tobacco disease, which has high risk of invasion in many areas, therefore, it is of particular importance to strengthen the quarantine work and to make a good prediction. Since each species has its own particular relatively stable ecological niche, one can predict the potential geographical distribution of tobacco blue mold in target areas like China. Based on the known distribution data of tobacco blue mold, 20 environmental factors were selected and combined support vector machine (SVM) with ecological niche model was used to predict the potential spatial distribution of tobacco blue mold and to obtain the optimal combination of SVM parameters through the brute force search algorithm. Search algorithm overcame the shortage of empirical method and improved the accuracy of prediction. The method was proved to be effective and feasible by cross validation which provided a robust theoretical basis for preventing the intrusion and spread of tobacco blue mold. Bangladesh J. Bot. 51(4): 883-888, 2022 (December) Special