Tension infiltrometer measurements have been used to measure steady‐state infiltration rates at applied tensions. The measurements can be used to determined soil hydraulic properties through linear or nonlinear regression. Such regression methods are often based on a few imprecise field measurements, and the traditional regression analysis may not yield valid estimates and reliable predictions. The objective of this study is to introduce fuzzy linear regression as an alternative to statistical regression analysis in determining hydraulic properties from tension infiltrometer measurements. Using a tension infiltrometer, in situ steady‐state infiltration rates [q∞(h)] were measured at six different tensions (h) between 3 and 22 cm of water on silty loam and clay loam soils. Hydraulic properties (i.e., field saturated hydraulic conductivity, Kfs, and inverse macroscopic capillary length scale, αG) and their confidence intervals were estimated following the fuzzy least‐square linear regression procedure with the minimum fuzziness criterion and linear least‐squares method (traditional statistical method). Both calculation procedures yielded the same mean hydraulic properties. A comparison between fuzzy and statistical ln q∞(h) relationship indicated that the confidence bands resulting from both procedures enveloped all the measurement points, but fuzzy regression estimates offered a tighter fit around the midpoint values (least‐square estimates). Fuzzy linear regression is more reliable and may be used as a complement or an alternative to statistical linear regression analysis for determining hydraulic properties from tension infiltrometer measurements.