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Net primary productivity (NPP) is a vital dataset to assess carbon cycling, carbon budget and interpreting global warming There are many approaches to calculate NPP, and Carnegie-Ames-Stanford approach (CASA) is one of the most popular approaches that was applied in this study. Black pine forest NPP was calculated with the CASA model in a transection zone between humid black sea and dry middle Anatolia region of Turkey for the year of 2016. Model parameters and homogeneity were tested with one-way ANOVA. Results was showed that annual NPP values were varied from 194 to 1213 (g C m(-2) year(-1)) for pure black pine stands. Model validation was made with stand increment, growing stock, and stand carbon values. Correlation co-efficiencies were obtained to be 0.92 and 0.85 respectively. It was found that NPP was higher in young stands where the mass accumulation potential was higher than areas, where crown closure was between 11% and 70%. According to this study, young stands should be established in the forests that were operated with the highest NPP objective. NPP models that can be used on a global scale is required intense data and time consuming In addition, it has been determined that mechanical models which are allowed more practical calculation and can be used with the stand parameters easily.