This study analyzes the impact of load condition and distance traveled on fuel consumption in a motorized-tricycle. It investigates whether the belief among tricycle drivers that more passengers result in additional income holds true, without considering the associated fuel costs. Real-time data was gathered using advanced sensors, a microcontroller, and storage media. The analysis utilizes the Multiple Correlation Formula to determine the strength of the relationship between fuel consumption, load condition, and distance traveled. The resulting Multiple Correlation Coefficient value (R) of 0.8154 shows a strong positive correlation between load condition, distance traveled, and fuel consumption. The Adjusted R Square value of 64.00% indicates that 64% of the variation in fuel consumption can be explained by these two dependent variables. Through Multiple Regression Analysis, a mathematical model is developed to predict fuel consumption based on the independent variables of load condition and distance traveled. The regression equation is represented as Y' = 0.6169 + 0.0066X1 + 0.0008X2, where Y' represents the predicted fuel consumption, X1 represents the load condition, and X2 represents the distance traveled. In summary, this study offers a comprehensive examination of the relationship between fuel consumption, load condition, and distance traveled in a motorized-tricycle. It sheds light on the economic implications of passenger and load weights on fuel costs.