The main objective of this research article is to propose linear programming problems for estimating the technical efficiency of DMU. This research article deals with the Shepard’s [1] input distance function and its properties are also evaluated. In addition to these extreme efficiency, efficiency but not extreme, weak efficiency and inefficient of a DMU are specifically examined here. In DEA the nature of returns to scale can be inferred. But we cannot quantify the returns to scale. The computations for the classification of RTS of a DMU are also derived in this discourse. In 2009, Barbara A. Mark et.al [2] in their paper, depicted an innovative method which is non-parametric to estimate technical efficiency. In 2011 S. Nuti et.al [3] inquired into the interrelations among technical efficiency scores, weighted per capita cost and overall performance. Gahe Zing Samuel Yannik et.al [4] used DEA to calculate technical assessment in banking sectors. In 2015 Smita Verma and others chosen a random sample of ten textile mills in India over the time period 2011-2013 and measures its technical efficiency using Data Envelopment Analysis.