Renewable energy systems integration in rural homes are increasingly seen as a solution to address energy poverty and environmental sustainability challenges. The study employs a mixed-methods approach combining quantitative regression analysis with qualitative interviews to assess costs, benefits, and impact factors related to solar PV integration in Zambian homes. A multinomial logit model is used to predict the likelihood of adopting renewable energy based on household characteristics. Solar PV adoption rates among households vary by income level: low-income households are more likely to adopt solar systems (60%) compared to higher-income households (45%). The developed methodology provides insights into the feasibility and effectiveness of renewable energy integration in Zambian rural settings. Policy recommendations include subsidies for lower-income households and community-based financing models to facilitate wider adoption of solar PV systems. Renewable Energy, Solar Photovoltaic, Rural Development, Economic Impact, Environmental Sustainability The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.