Fish growth models may help understanding the influence of environmental, physiological and husbandry factors on fish production, providing crucial information to maximize the growth rates of cultivated species. The main objectives of this work were to: i) develop and implement an Individual Based Model using a Dynamic Energy Budget (IBM-DEB) approach to simulate the growth of two commercially important Sparidae species in semi-intensive earth ponds, the white seabream which is considered as a potential candidate for Mediterranean aquaculture and the gilthead seabream that has been cultivated since the early 80s; ii) evaluate which model parameters are more likely to affect fish performance, and iii) investigate which parameters might account for growth differences between the cultivated species. The model may be run in two modes: the “state variable” mode, in which an average fish is simulated with a particular parameter set and the “Individual Based Model” (IBM) mode that simulates a population of n fishes, each with its specific parameter set assigned randomly. The IBM mode has the advantage of allowing a quick model calibration and an evaluation of the parameter sets that produce the best fit between predicted and observed fish growth. Results revealed that the model reproduces reasonably well the growth of the two seabreams. Fish performance was mainly affected by parameters related to feed ingestion/assimilation and reserves utilization, suggesting that special attention should be taken in the estimation of these parameters when applying the model to other species. Comparing the DEB parameters set of the two sparids it seems that the white seabream's low growth rates are a result of higher maintenance costs and a lower feed assimilation efficiency. Hence, the development of new feed formulations may be crucial for the success of white seabream production in semi-intensive earth ponds.