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In this study, thermal groundwater from arid area in southeastern Tunisia was assessed for irrigation use. For this purpose, thirty-one water samples were collected and physiochemical parameters (EC, pH, TDS, major ions) were measured and analyzed. A fuzzy logic model was developed in which six parameters were integrated: electrical conductivity, sodium adsorption ratio, sodium percentage, Kelly ratio, permeability index and temperature. The membership functions for a fuzzy logic model were developed using linguistic terms and trapezoidal shapes. The fuzzy logic model developed was validated with a dataset of chemical analyses from groundwater sampled in the study area. The assessment indicated that 26% of the samples were in the "good" class, 10% in the "good to permissible" class, 55% are in the "permissible" class, 6% are in the "permissible to harmful" class and 3% were considered to be harmful and therefore unsuitable for use in irrigation. The effectiveness, simplicity and robustness of the fuzzy model assessment make this approach a more consistent and reliable way of assessing water quality than conventional methods of assessing water quality data.