This paper presents and describes a methodology for morphology assessment, crystal particle classification and quantification of the complexity level of a crystal or a population of crystals. It further describes the application of such methodology to the study of the influence of MgCl2 in the crystallization of NaCl, namely on crystal size and morphology. Image analysis techniques are combined with discriminant factorial analysis leading to results that allow the computation of the complexity of crystals through a new parameter, the agglomeration degree of crystals. With this methodology it has been possible to distinguish automatically among three different classes of crystals, and within each class as per their complexity. Agreement between manual and automated classification measured in terms of a performance index is 90% on average. The effect of supersaturation and impurity concentration on the type, amount and complexity level of the agglomerates was further determined.