Antitubercular activity of 5-nitrofuran-2-yl Derivatives series were subjected to Quantitative Structure Activity Relationship (QSAR) Analysis with an effort to derive and understand a correlation between the biological activity as response variable and different molecular descriptors as independent variables. QSAR models are built using 40 molecular descriptor dataset. Different statistical regression expressions were got using Partial Least Squares (PLS),Multiple Linear Regression (MLR) and Principal Component Regression (PCR) techniques. The among these technique, Partial Least Square Regression (PLS) technique has shown very promising result as compared to MLR technique A QSAR model was build by a training set of 30 molecules with correlation coefficient ($r^2$) of 0.8484, significant cross validated correlation coefficient ($q^2$) is 0.0939, F test is 48.5187, ($r^2$) for external test set (pred$_r^2$) is -0.5604, coefficient of correlation of predicted data set (pred$_r^2se$) is 0.7252 and degree of freedom is 26 by Partial Least Squares Regression technique.