An algorithm that solves a linear program with planes exterior to the feasible region is described. Given a linear program in a standard form, a constraint derived from the objective function is added to make the program infeasible, the objective function is removed. The added constraint is incrementally and unidirectionally moved toward the solution vertex in cycles. On reaching the solution vertex the program becomes feasible, this signals both the solution of the program and termination of the algorithm. Because of unidirectionality, the algorithm is guaranteed to terminate. With N variables, B-bit fixed point arithmetic, and feasibility testing complexity of O(f(N)), the complexity of the incremental exterior plane algorithm is 2B O(f(N)). With binary search, the complexity is ~O(B f(N)). Feasibility checking may be done by finding the optimum of a related LP in each cycle. Unlike in established LP methods it is only necessary to know if an intermediate constraint set is feasible or not, neither the optimum of the related LP nor the basic feasible point obtained is used or needed. The algorithm works efficiently with deformed products. Thus with a 43-dimensional Klee-Minty cube (which would require > 1012 pivots with the simplex method) the solution is obtained in less than 100 binary search cycles, similar results are obtained with Goldfarb-Sit cubes. The exterior plane algorithm is compared qualitatively with the simplex, ellipsoid, and interior point algorithms and miscellaneous others. Â