In this research, a rule-based expert system named EFSIS-ES (Engineering Factors of Sprinkler Irrigation System -Expert System) had been built, verified and validated. Therefore, the aims of this research were to build, verify and validate an expert system for making a decision for the normal user to maximize system efficiency of sprinkler irrigation. The inputs data included location data, climate data, pump data, crop data, soil data and sprinkler system data. The outputs of the expert system were number of the sprinklers on a lateral, number of laterals in the irrigation system, length of each lateral, main line length, irrigation frequency, required pump power, total dynamic head (TDH) and pump discharge output. Results showed high correlation (R2 = 0.9927) between the EFSIS-ES program and the designed spreadsheet in regard to irrigation frequency. It could be indicated high correlation (R2 = 0.9999) between the EFSIS-ES program and the designed spreadsheet regarding pump power. The regression coefficient (R2) was 0.9983 between EFSIS-ES program and SSSDPS Expert regarding total dynamic head (TDH). It could be indicated high correlation (R2 = 0.9979) between EFSIS-ES program and SSSDPS Expert regarding pump discharge output.