This paper examines statistical approaches for interpolating market related data over large regions, providing different interpolation techniques for market access variables used in agricultural research. Splines interpolation process was evaluated to distribute different variables related to market accessibility for total land area of Papua New Guinea. Different independent market access variables like village points, minor market, major market, capital market, telecommunication, airstrip and airports, major road network and major wharfs, were used for the interpolation process. Suitable market access zones were modeled using each independent market access variable. The accessible area was coded as 1 and rest area as 2 for each case. Overlay operation (intersection and union) was performed to find out the suitable market access zones using previously modeled seven types of market accessibility results. Then the final market accessibility layer was classified into 3 categories as Good, Medium and poor access. These market accessibility characteristics were applied to all the villages of Papua New Guinea to determine the market accessibility zone for each of them. Rice crop suitability analysis was carried out for entire Papua New Guinea base on multi-criteria decision-making approach using slope and altitude, soil texture, water holding capacity, soil depth, soil drainage, pH, exchange base saturation, nitrogen, potassium, phosphorus, temperature and rainfall data sets. Finally overlay analysis was carried out between market accessibility and suitable agriculture land zones for entire Papua New Guinea to show the prospects of rice cultivation for marginal farmer in term of market accessibility.