Yield maps became economically feasible to farmers with the technological advances in precision agriculture. The evidence of its profitability, however, is still unknown and, rarely, yield variability has been correlated to profitable variability. Differently from yield maps, profitable maps can supply additional information related to the economical return for each particular area of the field. So, the objective of the present work was to study the economical viability in four situations, using profitable and profitability maps, as well as to quantify the influence of interpolator type (inverse of distance, inverse of square distance and kriging) used for data computation in these maps drawing. It can be concluded that profitable and profitability maps are important tools for the diagnosis of spatial variability of economic return, since they allow farmers on the management decisions-making. They also simulate the most appropriate crop for each given field within a rural property, through projections of prices for several different crops. Results for interpolation methods were practically identical and the interpolation through the inverse of distance was equivalent to interpolation by kriging. The correlation among maps was accomplished by average modulus deviation, coefficient of relative deviation and index kappa methods.