This study examines the impact of the manufacturing sector and human capital development on unemployment in Nigeria using the Autoregressive Distributed Lag (ARDL) model to analyze both short- and long-run dynamics. Utilizing annual data on unemployment rate (LUMR), manufacturing value added (LMVA), manufacturing sector growth rate (LMSGR), primary school enrolment (LPRE), and government expenditure on education (LGEE), the analysis confirms that the variables are stationary at level or first difference, validating the ARDL approach. A three-lag structure is selected based on lag criteria, and the results indicate that LMVA, LMSGR, and LGEE significantly influence unemployment in the short run, while their long-run effects are statistically insignificant. Nonetheless, the ARDL bounds test confirms a long run cointegrating relationship among the variables. Diagnostic tests show no evidence of serial correlation or heteroskedasticity, and CUSUM and CUSUMSQ tests confirm model stability. The findings suggest that while improvements in the manufacturing sector and human capital development can reduce unemployment in the short term, their limited long-run impact points to deeper structural issues. The study recommends policies aimed at strengthening the manufacturing sector through infrastructure and innovation support, alongside sustained investment in quality education and vocational training to address structural unemployment in Nigeria.