The Kriging model was introduced to detect and diagnose the faults in the chillers of building air-conditioning systems. This model was built and validated by using the normal data from ASHRAE RP-1043. The methods of T-statistic and exponentially-weighted moving average (EWMA) were compared by the sensitivity of performance indexes. The results show that the EWMA can achieve better performance sensitivity. Combined with the EWMA, Kriging model and the rules of fault diagnosis, the chiller faults like condenser fouling, refrigerant overcharge, refrigerant leakage, non-condenser gas, reduced evaporator water flow rate, and reduced condenser water flow rate were diagnosed using the measured data from ASHRAE RP-1043. The diagnosis results show that the chiller faults at different levels can be accurately and efficiently detected and diagnosed by using the Kriging model.