The physical and chemical properties of soils are known to greatly influence the forest communities that rely on them and dramatically shape the composition of the surrounding biotic communities. Unfortunately, soil sampling in the Ozark Highlands region of northern Arkansas is inherently difficult due to the rocky nature of the soil. Our project looked at the possibility of using blueberry (Vaccinium spp.) to predict soil nutrient concentrations based on foliar analyses because foliage is much easier to sample than the soil. Soil and foliage samples were collected from eight sites across the region during spring, summer, and fall. The samples were analyzed for their chemical characteristics using both chemical and near infrared reflectance spectrometry (NIRS) methods. Regression analysis indicated that chemical methods of foliar analysis did not predict soil nutrient concentrations well, with less than five percent of the variation being explained for each soil nutrient. NIRS analysis of the foliage did a much better job of prediction with over fifty percent of the variation found in soil N, C, P, Ca and pH being explained. NIRS analysis of the foliage was also used to predict leaf nutrient concentrations and it was highly effective for most plant nutrients. The foliage analysis was able to explain 99% of the variation for crude protein and 97% for phosphorus. The results highlight the potential of NIRS to become a powerful and cost effective tool for evaluating forest soil and plant chemical properties.