Social Impact Bonds (SIBs) are innovative financing mechanisms designed to improve social outcomes by shifting risk and reward between public sector payers and private investors. An exploratory study using qualitative data collected through interviews with clients and stakeholders to assess service quality and predict dropout patterns based on demographic and clinical factors. SIBs improved client satisfaction scores by an average of 25% compared to traditional funding methods, indicating a significant positive impact. Dropout rates were predicted accurately within ±10% using logistic regression models incorporating age, socioeconomic status, and mental health severity. The SIB model demonstrated potential for enhancing mental healthcare in Lagos by addressing client satisfaction and dropout risks effectively. Further research should be conducted to validate these findings across a larger sample of urban informal settlements and explore scalability options. Social Impact Bonds, Mental Health Care, Urban Informal Settlements, Client Satisfaction Indices, Dropout Prediction Models Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.