ABSTRACT: The two principal methods that have been used for estimating the Frontiers in the production theory are Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA), which involve mathematical programming and Econometric Methods respectively. DEA is a nonparametric linear Programming approach for measuring the relative efficiency of a Set of decision-making units (DMUs), which are using multiple inputs to produce multiple outputs. There are two different orientations of objectives in DEA namely input-orientation and output-orientation; two different DEA models based on scales namely Constant Returns to scale (CRS) and variable Returns to scale (VRS). Stochastic Frontier Analysis is the technique that has been used for estimating the frontier parametrically. This approach was used by Aigner and Chu (1968) who considered a Cobb-Douglas production frontier for estimating the Economic efficiency. Computing the efficiency measures involves estimating the unknown production frontier. This study has proposed the validity verification procedures through DEA & SFA for developing suitable Decision Support Systems (DSS) in the frontier Analysis. For the said objective, the study has considered the basic approaches of DEA like classical Charnes-Cooper-Rodes (CCR) model, classical Banker-Charnes-Cooper (BCC) model and Slack Based Measure (SBM) models along with different production functioning approaches like SFA.