We consider the approximation of two NP-hard problems: Minkowski Decomposition (MinkDecomp) of lattice polygons in the plane and the closely related problem of Multidimensional Subset Sum (kD-SS) in arbitrary dimension. In kD-SS we are given an input set S of k-dimensional vectors, a target vector t and we ask, if there exists a subset of S that sums to t. We prove, through a gap-preserving reduction, that, for general dimension k, kD-SS is not in APX although the classic 1D-SS is in PTAS. On the positive side, we present an O(n^3 / e^2) approximation grid based algorithm for 2D-SS, where n is the cardinality of the set and e>0 bounds the difference of some measure of the input polygon and the sum of the output polygons. We also describe two approximation algorithms with a better experimental ratio. Applying one of these algorithms, and a transformation from MinkDecomp to 2D-SS, we can approximate Mink-Decomp. For an input polygon Q and parameter e, we return two summands A and B such that A + B = Q' with Q' being bounded in relation to Q in terms of volume, perimeter, or number of internal lattice points, an additive error linear in and up to quadratic in the diameter of Q. A similar function bounds the Hausdorff distance between Q and Q'. We offer experimental results based on our implementation.