Landowner classifications based on their objectives have been used to describe the heterogeneous group of landowners. As the accurate information on landowners preferences is essential in policy planning and evaluation of the effects of various policy instruments, there is a need to develop feasible methods for classifying land owners. In this study we apply objective based classification to farmland owners using the data of Finnish farmland owners. We compare two classification methods, traditional cluster analysis and latent class analysis, in terms of their criterion validity. The comparison of criterion validity, consisting from convergent, concurrent, discriminant and predictive components of validity, revealed that latent class analysis was superior method. The analysis showed that objective grouping of farmland owners was relevant predictor of landowner behavior, and is thus valuable information for agricultural policy makers.