The study focused on the factors influencing jobless in Uganda and has the following goals: to ascertain the effect of the rate of population growth, the connection between price increases and youth joblessness, and the effect of foreign direct investment on youth unemployment. The study used descriptive information along with a design that was cross-sectional in nature. This study's goal was to pinpoint the elements that influence young people's unemployment in the Kampala region of Uganda. Before being applied for forecasting, the VAR model underwent time-series property. The time series data undergone a descriptive analysis to make sure that the distribution was normal. These included assessments of the center of gravity (mean, median, and mode) as well as a measure of variability (standard deviation, skewness, and kurtosis). As a pre-test for time series data, stationarity checks were carried out using unit root tests. The rate of unemployment and foreign direct investment were significantly correlated, with a somewhat favorable relationship, according to the Pearson correlation value of 0.566. The null hypothesis was rejected and it was found that there was a significant correlation between foreign direct investment and the rate of unemployment since the P-value (0.00) 0.05 showed that this link was statistically different at the 5% level of importance. Similar to this, the correlation value of -0.203 revealed a weak negative insignificant relationship between the rate of joblessness and population growth. R-squared is 0.355, which indicates that 36% of the variations in unemployment can be attributed to population growth, inflation, and foreign direct investment. Other elements discovered in the error term provide 36% of the interpretation; as a result, they are not included in the model. The data is well-fitted, and since the R2 is high, the fit is also good. The research.miu.ac.ug/publications 1047 METROPOLITAN JOURNAL OF BUSINESS & ECONOMICS (MJBE) ISSN 1813-4238 Vol. 2 Issue 4, July - 2023, Pages: 1047-1067 F statistic of 6.057 with a p value of 0.002, which is less than 0.05, suggests that every factor together have a substantial short-term impact on unemployment. The data is well-fitted and consequently a good fit because the R2 is high.