A good number of stimulations tools reproduce the deterministic physical behaviour of buildings especially in lighting with repeated standard patterns of occupant presence without replicating the dynamic occupancy and activities associated with such environment. This thereby contributes to peak energy/demand crisis being experienced in countries and over estimation of energy savings associated with energy (lighting) efficient projects that have been embarked upon by utilities or government. This research work involves the comparative and performance assessment studies of an ANFIS-based model that is capable of addressing and solving non-linear issues, ambiguity and randomness of data to ensure adept estimation and prediction of lighting load profiles. The proposed technique is based on learning and adaptation of the variables associated with lighting usage. Two different investigative approaches were applied in relation to the ANFIS-based model for domestic lighting profile development. Validation process was carried out in terms of the model profiles to ascertain the performance of the methodology. Good correlation and coefficient of determination in comparison with the actual output; better correlation in comparison with other research studies and models was also deduced. This technique is expected to assist utilities, energy and measurement and verification practitioners as well as contribute to lighting load profile modelling. (C) 2015 Elsevier B.V. All rights reserved.