The study was conducted to determine the best model suitable for the determination of ferrum uptake in Brassica chinensis (flowering white cabbage). A nonlinear regression model was selected to determine the amount of ferrum absorbed by each part of the Brassica chinensis plant namely the leaves, stems and roots. The Levenberg-Marquardt method was used to perform the nonlinear least square fit. This method employs information on the gradients and hence requires specification of the partial derivatives. A suitable model was obtained from the exponential regression model. The polynomial model was found to be appropriate for leaves, the mono-exponential model was suitable for stems and the simple exponential model for roots. The residual plots and the normal probability plots from each of the models indicated no substantial diagnostic problems, so it can be concluded that the polynomial and exponential regression models provide adequate fit to determine data on heavy metal uptake by the flowering white cabbage.