The size distribution as a function of weight of particles is an important measure of product quality in the mining and aggregates industries. When using manual sampling and sieving, the weight of particles is readily available. However, when using a machine vision system, the particle size distributions are determined as a function of the number of particles. In this paper we first show that there can be a significant weight-transformation error when transforming from one type of size distribution to another. We also show how the problem can be overcome by training a classifier and scaling the results according to calibrated average weights of rocks. The performance of the algorithm is demonstrated with results of measurements of limestone particles on conveyor belts.