VANETs are mobile wireless networks anywhere nodes are vehicles. It is to permit vehicles to converse with all others. A car must transmit its data to other vehicles which requires enough resources to improve communication. During communication, load balancing is defined as the process of distributing the network traffic across multiple servers. Issue of load blockage frequently happens at minimum bandwidth resulting in increased latency, reduced missing packet rates, and increased battery power consumption. Method Used: A novel technique called a Multi-Objective Rainfall Drop Resource Optimized Censor Regressive Load Balancing (MODEL) technique is developed in VANET. The MORDEL includes two different processes namely multi-objective gradient Elitist rainfall drop optimization and Shapiro–Wilk test censored regression. First, the numbers of vehicle nodes are disseminated in a wireless network. Then optimization process is carried out to select resource efficient node for load balancing. The optimization process starts with an initial population of raindrops. After the initialization, the movement of water drops created through rainfall is identified to optimize the fitness function based on multi-objective functions. It are related to resource of vehicle nodes such as energy as well as bandwidth. Then, vehicle nodes by enhanced residual energy and bandwidth are chosen as optimal vehicle nodes for load-balanced data transmission in the VANET. With the selected optimal vehicle nodes, Shapiro–Wilk test censored regression is applied to find the load of each node. In the regression analysis, the dependent variable (i.e. load of the vehicle node) is censored above or below a certain threshold. As a result, the lesser load and higher load capacity of the vehicle nodes are identified. After that, the heavily loaded vehicle node transmits its load to the nearest lesser-loaded vehicle node for minimizing the delay and loss of data transmission. The Manhattan distance measure is used to find the nearest lesser-loaded vehicle node. Resource efficient load-balanced data transmission is carried out in VANET Results Achieved: Simulation of the proposed MORDEL technique is implemented through various performance metrics with respect to number of data packets and vehicle nodes. MORDEL technique improved packet delivery by 17%, throughput by 28% and reduces end-to-end delay by 17% ,packet loss ratio by36% when compared to other existing load balanced techniques in VANET. Conclusion: Analyzed outcomes indicate which proposed MORDEL method improves performance of packet delivery ratio and minimum loss rate when compared to conventional works.