A chemical sensor is a device for measuring low concentrations of chemical solutes in a solution. Four different plant tissue sensors were used to measure the concentration of dopamine in aqueous solution. A mathematical model describing their transient characteristics was developed and experimentally verified. The rate parameters of the sensing process were determined by combining the present transient-state model with the analytical solution of a previously reported steady-state model. This combined approach simplified significantly the numerical solution of the transient-state model from a five to a two unknown parameters problem. A total of 285 transient response-time curves containing 34,911 data points were obtained experimentally with four different tissue powder dopamine sensors over a wide range of operating conditions. One hundred and ninety of them containing 18,573 data points were used for the numerical regression analysis and evaluation of the rate parameters. The remaining 95 sets were compared with the results predicted by the model using the regressed rate parameters. Good correlation and prediction were obtained confirming the adequacy of the model in describing the transient behavior of the biosensors and also the effectiveness of the combined models approach in the computation. The results facilitate the optimum design and fabrication of such sensors.