In crops management, it is important to estimate the damage effected by pests since the degree of damage will determine the level of pest activity. Pest activity usually involves their life stage and its presence in the field. In addition, pest management in crops is a crucial problem and may yield losses if it is not handled properly. Consequently a forecasting tool is needed to predict the level of pest activity. This is important so that an early treatment or action can be applied before more damage to the plant occurs. Accordingly, the fuzzy expert system may facilitate the user through a consultation session in order to forecast the pest activity in the rice field. A set of questions will be asked to help users diagnose their given symptom in order to infer such a conclusion. Figure 1 shows the main components of an expert system including inference engine, expert, knowledge base, working memory, and user interface. The consultation performed by the expert system also involves fuzzy logic to deal with the natural and uncertainty data. Besides, all the information and knowledge about the pests, treatment control measures and prevention steps are managed in the specific knowledge base created in the system. This system is able to educate and inform the farmers and smallholders about pests and their activities in the rice field.