UNDERSTANDING the spatial variability of soil properties is essential for effective nutrient management, especially in organic farming systems that rely on natural inputs and ecological processes. The study was conducted in 2022-2023 at the Deen Dayal Upadhyay Centre of Excellence for Organic Farming, CCSHAU, Hisar, India, a semi-arid region with an aim to characterize and map the spatial variability of key soil fertility parameters. Eighty-nine surface soil samples were collected and analysed for various physico-chemical parameters. Geostatistical methods, principal component analysis and fuzzy c-means clustering were employed to evaluate and map soil fertility across the farm. Soils were neutral to alkaline, exhibited variable salinity and had medium to high levels of soil organic carbon, available phosphorus and potassium, but were low in nitrogen. Semivariogram modelling showed that exponential and spherical models best described spatial variability, with strong spatial dependence for all properties, indicating the dominance of structural factors. Ordinary kriging maps revealed clear east-west gradients in soil fertility related to topography and land-use systems. Principal component analysis found three major components that explained the variance of 83.66%. The fuzzy c-means clustering identified six soil management zones that had a great variation in fertility parameters. The western zones were characterized by high pH and salinity and low nutrient conditions associated with inadequate drainage and salinity stress whereas the eastern regions demonstrated improved fertility associated with high organic inputs. The study also demonstrates the usefulness of spatial statistics and multivariate analysis in mapping the soil fertility in order to provide site specific management that will enhance input efficiency, maintain productivity and facilitate sustainable organic farming in semi-arid areas.