For millennia, land use in the Mediterranean region has led to situations in which soil has been severely degraded showing high risks of erosion and impoverishment. Thus, the establishment of soil quality indices is considered to be of crucial importance in determining the state of degradation and recovery of soils. Soils from stable forest ecosystems have specific physical, chemical and biological properties due to the conditions in which they developed. Hence, modelling the balance established among different key soil properties from stable forest ecosystems could be used as a soil quality index, because disturbance practices lead to changes in that natural balance. Here we report the establishment of two soil quality indices under Mediterranean semiarid conditions for forest soils in SE Spain, based on the use of multiple linear regressions integrating different physical, chemical and biochemical properties. As we observed the strong influence that climatic factors have on the values of the different soil properties and their relationships, mean annual precipitation was also incorporated in the regression models as a categorical explanatory variable. Model 1, that explains 92% of the variance in soil organic carbon (SOC), showed that SOC can be calculated by a linear combination of 6 physical, chemical and biochemical properties (acid phosphatase, water holding capacity (WHC), electrical conductivity (EC), available phosphorus (P), cation exchange capacity (CEC) and aggregate stability (AS)). Model 2 explains 89% of the variance in SOC, which can be calculated by means of 7 chemical and biochemical properties (urease, phosphatase and β-glucosidase activities, pH, EC, P and CEC). Our results confirm that a balance exists between the soil organic carbon of high quality soils and some other properties widely recognised in soil quality assessments, due to their sensitivity and the information they provide about the functionality of soils. As disturbance practices should be accompanied by the loss of this balance, SOC calculated by the models (SOCc) is no longer an accurate estimation of the actual SOC determined in laboratory (SOCa). Thus, it is possible to obtain a soil quality index by the calculation of the model residuals: Soil Quality Index=model residual=SOCc–SOCa. For a non-disturbed soil, the soil quality index should be 0 (SOCc=SOCa). In contrast, for disturbed soils, SOCc should be lower or higher than the actual SOC, with values in the soil quality index 0.