The pharmacokinetic properties of chitosan nanoparticles have been shown to mainly depend on its particle size. The aim of this study was to concurrently evaluate and model the effective parameters, namely, chitosan concentration, buffer pH, amplitude and time of sonication, on the particle size of chitosan nanoparticles. Chitosan solutions were prepared and sonicated with different values for the above mentioned parameters. The data were then modeled using artificial neural networks (ANNs). The results illustrated that all four input parameters affect the size of prepared chitosan nanoparticles. While a reverse effect was observed between the size and the buffer pH as well as time and amplitude of sonication, the concentration was found to directly influence the particle size. The optimum condition to obtain the minimum size of nanoparticles in the range of 50-200 nm was found to be high values of pH and sonication time (i.e. approximately 4.9 and 500 s, respectively) and amplitude values of more than ~55.