<![CDATA[This study aims to decide the factors that influence Road fatalities per one million inhabitants in member countries of the Organization for Economic Co-operation and Development (OECD). This research data uses a dataset covering 19 member countries of the Organization for Economic Co-operation and Development in 2010 – 2018. This research method uses multivariate analysis with multiple linear regression techniques using several indicators. Nine independent variables are used in this model, namely (X1) road passenger transport in passenger-km per one thousand units of current Gross Domestic Product (GDP) United States Dollar (USD), (X2) road freight transport in tonne-km per one thousand units of current Domestic Product (GDP) United States Dollar (USD), (X3) density of road (km per 100 sq. km), (X4) road transport infrastructure investment in constant United States Dollar (USD) per inhabitant, (X5) goods road motor vehicles per one thousand inhabitants, (X6) motorcycles per one thousand inhabitants, (X7) passenger cars per one thousand inhabitants, (X8) road motor vehicles per one thousand inhabitants, (X9) road traffic in thousand vehicle -km per road motor vehicle. One variable (Y) road fatalities per one million inhabitants, as the dependent variable. The results of the analysis showed that the independent variables had a partial significant effect on road fatalities. From the validation results obtained the value of R² the model is 60%, the F-statistic is 16.03 with a significance value of 0.0000 and the correlation value of the model is 0.66. The resulting multiple regression analysis model is: Y = 69.3071 - 0.0936.X1 + 0.1225X2 + 0.0020X3 - 0.0484X4 + 0.2070X5 + 0.3829X6 - 0.0364X7 -0.0354X8 + 0.0010X9]]>
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