Background: We examined whether Multidimensional poverty index (MPI) explained variations in life expec-tancy (LE) better than income poverty; and assessed the relative importance of MPI indicators in influencing LE. Methods: Cross-sectional data from 62 developing countries were used to run several multivariate linear regres-sions. R2 was used to compare the powers of MPI with income-poverties (income poverty gaps [IPG] at 1. 9 and 3. 1 USD) in explaining LE. Results: Adjusting for controls, both MPI (β =-0. 245, P<0. 001) and IPG at 3. 1 USD (β =-0. 135, P=0. 044) sig-nificantly correlates with LE, but not IPG at 1. 9 USD (β =-0. 147, P=0. 135). MPI explains 12. 1% of the variation in LE compared to only 3. 2% explained by IPG at 3. 1 USD. The effect of MPI on LE is higher on female (β =-0. 210, P<0. 001) than male (β =-0. 177, P<0. 001). The relative influence of the deprivation indictors on LE ranks as follows (most to least): Asset ownership, drinking water, cooking fuel, flooring, child school attendance, years of schooling, nutrition, mortality, improved sanitation, and electricity. Conclusion: Interventions to reduce poverty and improve LE should be guided by MPI, not income poverty indices. Such policies should be female-oriented and prioritized based on the relative influence of the various poverty deprivation indicators on LE.