MULTIVARIATE DATA MAY INCLUDE MISSING VALUES FOR VARIOUS REASONS. MISSING VALUES CAN BE ESTIMATED USING DIFFERENT APPROACHED, SUCH AS INTERPOLATION, NIPALS LIKE PROCEDURE AND ETC [1].A MAIN GOAL IN THE CALIBRATION METHODS SUCH AS CLS, ILS, PCR AND PLS IS THE PREDICTION OF UNKNOWN SAMPLES USING THE ESTIMATED MODEL [2]. IN THIS STUDY MULTIVARIATE CALIBRATION PURPOSES IS ACHIEVED BY USING MISSING VALUES ESTIMATION STRATEGIES. CONSEQUENTLY, MULTIVARIATE PREDICTION OF UNKNOWN SAMPLES IS POSSIBLE WITH NO NEED TO CONSTRUCTION AND APPLICATION OF CALIBRATION MODELS.STANDARD ERROR OF PREDICTION (SEP) SET AS THE CRITERION FOR EVALUATION OF THE PROPOSED METHOD. FOR THIS PURPOSE NIPALS, KIERE, WOLD, AND ITERATIVE IMPUTATION METHODS WERE EXAMINED. FINALLY THE SEP OF CALIBRATION METHODS WERE COMPARED WITH THE SEPS FROM THE PROPOSED METHOD. AMONG THE CALIBRATION MODELS, PLS RESULTED IN LOWEST SEP VALUES.THE METHODS OF HANDLING MISSING VALUES WERE SUCCESSFULLY USED AS FOR CALIBRATION TRANSFER PURPOSES [3], AS WELL. CALIBRATION TRANSFER IS UTILIZATION OF CALIBRATION MODEL FROM ONE CONDITION TO ANALYSIS THE DATA OF A SECOND CONDITION. TRANSFER OF CALIBRATION FROM ONE INSTRUMENT TO ANOTHER IS AN EXAMPLE. A NOVEL POINT IN THIS APPROACH IS THE POSSIBILITY OF CALIBRATION TRANSFER IN THE ABSENCE OF TRANSFER SAMPLES, WHICH IS AN ADVANTAGE TO COMMON CALIBRATION TRANSFER TECHNIQUES.