Digital credit access strategies are crucial for enhancing financial inclusion among unbanked populations in coastal regions of Kenya, particularly addressing economic disparities and promoting sustainable development. A mixed-methods approach combining quantitative surveys with qualitative interviews was employed to gather comprehensive data from a sample population. Statistical models were used to analyse credit access success rates and predict future trends using logistic regression analyses. The preliminary findings indicate that digital credit usage among unbanked individuals increased by 20% after financial literacy workshops, suggesting positive engagement with digital solutions. This study validates the potential of targeted digital credit strategies in promoting financial inclusion and economic growth within Kenyan coastal communities. Policy makers should invest in scalable digital infrastructure to support continued access and adoption of innovative financial services among unbanked populations. 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.