Abstract: Background and Objective: In literature there has been a study on ratio cum product estimator of a finite population mean in two-phase sampling in sample surveys, but it lacks study when there is non-response on sample observations. So the main objective of this paper was to propose three generalized classes of ratio cum product compromised imputation techniques in presence of missing values in two-phase sampling design and its properties have been studied. Materials and Methods: The estimators were compared with other existing estimators in two different designs. The bias and M.S.E. of suggested estimators were derived in the form of population parameters using the concept of large sample approximations. Results: The results showed the superiority of the proposed estimators over the existing methods. Numerical studies are performed over two population data sets using the expressions of bias and M.S.E. and their efficiencies are compared with other existing estimators. Conclusion: It was observed that the proposed estimators were performing better than the estimators taken for comparisons in the presence of missing data.