The chemistry of individual grains of several Class F fly ashes has been investigated by electron microprobe analysis. To interpret the analytical data-set, a combination of two multivariate statistical procedures was applied. The method involves the use of both fuzzy c-means cluster analysis (FCM) and non-linear mapping (NLM). It allows for a quick visual interpretation of the fly ash analysis and provides information which is not obtained through the use of the commonly used classical two-or three dimensional data representation plots alone. The method provides information on the occurrence of “outlying” samples, such as quartz grains, lime, calcium-sulfate or iron-containing particles. When the data-set is truncated for these outlying particles, cluster analysis of all ash data indicates that a model of 4–5 clusters can best explain chemical differences between the bulk of the particles of several class-F fly ashes. These clusters are related to each other by an inverse relation between the SiO2 and the A12O3 content, and some clusters display marked differences of either the oxides of Ti, Fe, Ca, Mg, K and/or K and Na. Inter-grain variation of one separate fly ash indicates that similar variations occur within individual fly ashes, only the absolute differences being smaller. The results are interpreted to represent either the coalescence or fusion of chemically different particles or small chemical differences in precursor clay minerals. The method of data-reduction presented here provides quick information on chemical relationships and is particularly suited to evaluate small data-sets. The method has potential to be combined with other input parameters, such as pozzolanic activity, glass content, particle size distribution and others.