This work presents a grid-based fuzzy expert system environment, which employs a repertory grid, fuzzy theory and case-based reasoning. The proposed environment provides friendly user interfaces, abundant data types, intelligent knowledge acquisition facilities and an efficient inference engine. To help users make precise decisions, three factors (i.e., feasibility, reliability and certainty) are used during inference. Moreover, several tools are provided to help experts define membership functions and the knowledge of multimedia data types. Furthermore, the proposed approach is evaluated by implementing an expert system for the diagnosis of animal diseases and by performing several tests.