We investigate the aggregation of gold nanoparticles using both experimental and numerical techniques. First, the uniform gold nanoparticles are prepared by citrate reduction method. To induce aggregation of these nanoparticles, we replace the surface groups on these particles. Changing the surface groups leads to the change in the interparticle interaction, which results in the aggregation of particles. We monitor the aggregation process using various experimental techniques and use the classical DLVO theory to rationalize the experimental results. For a quantitative understanding of the aggregation process, we solve the population balance equations using the constant-number Monte Carlo method. In this method, total number of samples is kept constant during simulation to allow long simulation without loss of accuracy. The classical DLVO theory is used in the calculation of aggregation kernel between particles of different sizes. We find that the experiments and the calculated results agree reasonably well.