Today’s automobiles include more electronics features and functions than at any time in history. From engine controller to crash sensing and passenger protection, all the way to automated driving, a complex network of electronic sensors and controls is being integrated into most of the vehicles. While many of these are necessary for increased comfort, convenience and safety, they must also be designed for the stringent quality requirements compared to standard consumer electronics. The business driven need for miniaturization with increased functionality but at reduced cost necessitates use of high density interconnection with advanced electronics components like Ball Grid Array (BGA) instead of many chip scale packages, which are potentially susceptible to failure while handling and shipping of the components. With the reduced mass of the component, accidental drop from the hand level would experience higher impact loading on the component to create significant damage. The usage of experimental approach to test out every possible design variation and identifying the one that gives the maximum design margin is often not feasible because of product development cycle time and cost constraints. Hence there is a fundamental need for understanding and predicting the failure mechanism during drop-impact using analytical approach.The objective of this paper is to develop system level simulation methodology to predict the failure of BGA package during drop test for an automotive electronic controller. The scope of the study focuses on correlating the simulation predicted response of the Printed Circuit Board (PCB) with experimental results. The design optimization study also has been conducted to investigate the optimum pad/adhesive thickness below the package to qualify product for a given drop condition. Finally, the key design modification like PCB thickness, pad thickness, effect of under-fill, pedestal size and location etc. has been suggested to mitigate the failure risks. This study has been adopted in various controller designs in investigating reasons for device failure and recommending the design modification.