This report describes an approach for developing conditional projections of the U.S. farm structure. The traditional approach to projecting the distribution of farms by size uses a Markov model with stationary (constant) transition probabilities. Although a useful tool for extrapolation of current trends, the stationary Markov approach cannot model the impacts on farm structure of varying economic and social causal forces. Data are now available for developing Markov models with nonstationary transition probabilities. In this document, a simple nonstationary Markov model of U.S. farm structure is described and estimated and its performance in predicting actual changes in farm numbers and sizes through 1986 is assessed. The nonstationary Markov model makes fuller use of the information available and generates a path of structural change that seems closer to what actually occurred after 1978. (Author/KC)