The need to achieve reliable and effective automatic control systems has directed numerous research efforts towards the development of assessing and monitoring methods of closed-loop performance. The primary contributions of this thesis are to (a) develop new informative and judicious assessment indices for the performance of univariate and multivariate controllers, which will offer additional and more reliable information than the existing indices; and (b) employ an accurate closed-loop identification methodology, which will provide accurate system models, which are necessary for the estimation of the proposed assessment indices. The Relative Variance Index (RVI) is the basis of the proposed controller performance assessment methodology. It is based on the comparison of the actual closed-loop variance with the best theoretical control action (minimum variance control) and no control action. The estimation methodology of the RVI from closed-loop data is the other key contribution which is highlighted throughout this thesis.