This paper presents an artificial neural network model for solid desiccant rotary system to predict its performance in terms of temperature and relative humidity of process air leaving the desiccant wheel after losing latent heat. Present paper also explains the experimental test setup that is used for taking reading. The experimental readings are all taken at steady state by varying the input conditions such as process air inlet velocity, regeneration air inlet velocity and regeneration temperature and process air inlet temperature and relative humidity. Majority of data taken from experiments is used to train the model (85%) and rest (15%) is used for testing of the model. The performance output predicted by the ANN model have high correlation factor(R>0.98336). The results predicted by the ANN model shows that ANN model can be successfully applied to predict the performance of solid desiccant wheel with sufficient accuracy and reliability. © Published under licence by IOP Publishing Ltd.