One of the important alternative water resources for non-potable purposes is greywater (GW), which must be cleaned of contaminants. In this regard, the clustering analysis of materials consisting of sand (S), zeolite (Z), peat (P) and granular activated carbon (GAC) within a horizontal series filter (HSF) was used for removal of chemical oxygen demand (COD), biochemical oxygen demand (BOD), total dissolved solids (TDS), and turbidity in GW taken from the Fasa University Student Hostel, Iran. The hierarchical clustering technique was applied to classify the adsorbents. The findings indicated that there were significant differences (more than 95%) between these materials. According to the similarity of level 95%, for COD, BOD, TDS, and turbidity removal, these adsorbents could be separately clustered in three, three, two, and three clusters, respectively. In addition, by considering the simultaneous changes of COD, BOD, TDS, and turbidity together, these adsorbents could be clustered in three different clusters. This paper proposed an efficient method to select the best combination of adsorbents for eliminating of COD, BOD, TDS, and turbidity from GW. Generally, based on the quality of treated greywater and literature, reusing greywater can be implemented for agriculture, artificial recharge of aquifers, desertification, and preventing the dust creation in arid areas such as southern Iran.