Vibrations on helicopter induced in Main Rotor System and Tail Rotor System due to in plane unbalanced masses and out of plane rotation of rotor blades. Rotor Track and Balance (RTB) of helicopter is performed to reduce vibrations of helicopter. Number of vibration flights will increase if RTB is not optimised. Main Rotor and Tail Rotor vibrations can be reduced by predicting the vibrations prior to flight using Multiple Linear Regression and Analysis of Variance (MLR & ANOVA). The Inputs for the Multiple Linear Regression would be in terms of mass changes, track changes and tab changes based on established sensitivities of these Inputs and cross sensitivities between them. The outputs are vibration changes of Main Rotor / Tail Rotor. Change in vibrations is the difference between the vibration values of two successive flights / ground runs. For Main Rotor, there are 12 inputs to adjust 2 outputs (MR Lateral and MR Vertical), for Tail Rotor, there are 8 inputs to adjust 2 outputs (TR Radial and TR Axial) for satisfactory vibrations during ground run, HOGE and two steady speed forward flight regimes. In this Research work, three types of Regression Models for Main Rotor System and Two types of Regression Models for Tail Rotor System were made to predict the vibrations of helicopter prior to ground run or flight. The Regression Coefficients were evaluated using MatLab and models were generated. ANOVA is performed for regression models and found satisfactory. The Coefficient of Regression (Multiple-R / R 2 ) values obtained are more than 0.9. The results of the regression indicated that the model was a significant predictor of vibration changes. Graphical User Interface (GUI) using Regression Models is made for vibration predictions of Main Rotor and Tail Rotor Vibrations of Serviced helicopter. This research work recommends for the implementation of Multiple Linear Regression and its applications for vibration predictions of Serviced helicopters to reduce vibration fl