The Direct Weight Optimization (DWO) approach to statistical estimation and the application to nonlinear system identification has been proposed and developed during the last few years. Computationally, the approachis typically reduced to a convex (e.g., quadratic or conic) program, whichcan be solved efficiently. The optimality or sub-optimality of the obtained estimates, in a minimax sense w.r.t. the estimation error criterion, can be analyzed under weak a priori conditions. The main ideas of the approach are discussed here and an overview of the obtained results is presented.