This article examines the rational use of natural and land resources based on intelligent methods for soil condition assessment. Special attention is given to the problem of soil salinity as one of the key factors reducing agricultural production efficiency and land use sustainability. The proposed model for assessing soil salinity degree is based on Mamdani fuzzy logic with Z-numbers application, which allows accounting for both interval uncertainty of indicators and reliability of expert information. We look at some key soil traits that matter for farming and ecology—like temperature, moisture, pH levels, and electrical conductivity. When it comes to figuring out how salty the soil is, we don’t just give a single number. Instead, we present a range of possible values along with a probability that shows how confident we are in that estimate. To make sense of the uncertainties, we built a fuzzy rule system that helps us assess soil conditions more holistically, even when the data isn’t crystal clear. The obtained results show that the proposed approach improves the validity of decision-making in rational land resource management, planning reclamation activities, and selecting soil treatment technologies. The model can be used in soil condition monitoring systems and environmentally-oriented natural resource management.