This work aims at evaluating a utilization of diverse clay mineral/gold nanoparticles/acetylcholinesterase (clay/ AuNPs/AChE) biosensors by using principal component analysis (PCA) for the discrimination of pesticide types and their concentration levels both in the synthetic and real samples. Applications of simple and low-cost clay/AuNP composites of different characteristics as modified-electrode materials are highlighted. Four types of clay minerals, namely, platelike kaolinite (Kaol: 1:1 aluminum phyllosilicate), globular montmorillonite (Mt: 2:1 aluminum phyllosilicate), globular bentonite (Bent: 2:1 aluminum phyllosilicate), and fibrous sepiolite (Sep: 2:1 inverted ribbons of magnesium phyllosilicate), were selected as the base materials. Due to the distinct characteristics of the selected clay, the derived clay/AuNP composites resulted in different physical morphologies, AuNP sizes and loadings, matrix hydrophobicity, and active AChE loading per electrode. These, in turn, caused divergent electrochemical responses for the pesticide determination; hence, no other enzymes apart from AChE were necessary for the fabrication of distinct biosensors. Physical and chemical characterizations of clay/AuNPs were conducted using scanning electron microscopy, transmission electron microscopy, thermogravimetric analysis, and X-ray photoelectron spectroscopy techniques. The electrochemical information was recorded by cyclic voltammetry and amperometry techniques. The enzyme inhibition results obtained from the pesticides were treated and used as input data to obtain PCA results. The four fabricated clay/AuNPs/AChE biosensors were able to discriminate chlorpyrifos and carbaryl and their concentration levels for synthetic pesticides and real samples. It was disclosed that a high enzyme inhibition and a high hydrophobic modified-electrode material affect a highly sensitive pesticide biosensor. The hydrophobic/hydrophilic character of the modified-electrode material plays a major role in discriminating the pesticide types and their concentration levels by the proposed single-enzyme sensor system. The PCA results illustrated that PC2 described the different types of pesticides, and PC1 showed the level of pesticide concentration with high first two principal components. The mixed pesticides could be identified at an especially low total concentration of 0.5 ng/mL in real samples.