This study describes three methodologies to generalize the multivariate estimators (A, U, Θ) taking into account the relationships between two or more dependent variables. These generalizations give answers to various modeling problems in geosciences by using the possible diversity for the univariate case between those that stand out the Kriging, the Radial Base Functions, the Inverse Powers of the Distance and the classic Polynomial Interpolators. The simultaneous estimator of dependent variables that is defined constitutes a systemic and powerful tool for multiple modeling. In this case, the expression is also described to approximate the multivariate estimation error. The algebraic approach that is presented in all cases permits programming these mathematical tools that are applied to the modeling wind parameters in two case studies.