Auxiliary information plays an important role in survey sampling, enhancing the precision, accuracy, and efficiency of estimating population parameters. This study focuses on the estimation of the finite population mean through the introduction of generalized ratio-type estimators in simple random sampling without replacement. These estimators utilize the coefficient of variation and population deciles. The paper calculates and compares the expressions for mean square error and bias with those of classical and existing estimators. The comparative analysis demonstrates that our proposed class of estimators qualifies as efficient estimators based on mean square error (MSE) and percent relative efficiency (PRE) criterion. Empirical findings affirm the efficiency of our proposed estimators over classical and existing ones, as they exhibit lower mean square error and bias. Additionally, the percent relative efficiency (PRE) is consistently higher in our proposed estimators