The assessment of forest productivity at early stages of stand development may help to define the most appropriate silviculture treatment to be applied for each stand. Site index (dominant height at a reference age) is a useful tool for forest productivity estimation. The aim of this study was to develop a model to predict site index for Scots pine (Pinus sylvestris L.) plantations in northern Spain acidic plateau by using soil (physical, chemical and biochemical), climatic and physiographic parameters. To meet this objective, data from 35 stands classified into three different site quality classes and 63 soil, climatic and physiographic parameters were examined in order to develop a discriminant model. After selecting 12 discriminant models which were biologically consistent and presented the higher cross-validated rate of correct classification, a model including four parameters (latitude, inorganic Al, porosity and microbial biomass carbon) as predictors was chosen. The discriminant
model classified 71% of cases correctly and no inferior-quality stands were misassigned to the highest quality class. Soil and physiographic parameters included in the above model are easily obtainable in the field or by simple laboratory analysis, thus our results can be easily integrated in operational forestry to determine site quality.