In the realm of intelligent transportation, the global logistics and supply chain industry grapples with the challenges of the transportation of perishable goods. This paper advocates for the optimization of perishable goods transportation through the application of Monte Carlo Simulation, a sophisticated tool to analyse traffic patterns and refine route selection. Targeting decision-makers, the study aims to unravel the intricate relationship between traffic dynamics, route choices, and product perishability. Historical traffic data, perishability rates, and route information are the basis for simulating the impact of traffic hours on goods perishing. The model actively seeks routes that minimise perished goods, employing Monte Carlo simulation to quantitatively assess the risks and benefits of various strategies. By presenting a data-driven framework, the research enhances supply chain efficiency, curbs losses of perished goods, and encourages the adoption of sustainable and intelligent transportation methods within the industry.