This paper analyzes a database of over 18,000 women micro-finance clients of the Negros Women for Tomorrow Foundation (NWTF), a database using the Progress Out of Poverty (PPI) Scorecard as a measure of poverty. Analysis using both OLS and quantile regression models shows how observable characteristics of borrowers affect the ability of clients to reduce their measured poverty. Loan size, duration, and the economic activity supported all have strongly identifiable effects. Moreover, estimates suggest which among the poor are receiving the greatest effective help by the program. Results offer advice to the NWTF and offer insight useful to policymakers and other micro-lenders.