A direct optimization method to estimate nucleation and crystal growth rate parameters from seeded batch cooling crystallization experiments is evaluated. The experimental information applied comprises the concentration of the solution and the temperature as functions of time and the final product size distribution. Parameters in kinetic equations are determined by nonlinear optimization of a dynamic model of the experiment, by which intermediate approximations of experimental data are avoided. The optimization objective function includes both solution concentration data and product size distribution data. Kinetics are estimated for succinic acid crystallizing in aqueous solutions. Results from several different cooling crystallizations are simultaneously supplied into one single optimization to determine seven parameters.