Real estate portfolio valuation plays a critical role in unlocking funding for affordable housing projects. Investors, financial institutions, and policymakers rely on accurate valuation techniques to assess risk, determine asset value, and allocate capital efficiently. This study examines various valuation methods and their application in securing funding for affordable housing initiatives. Key valuation techniques include the cost approach, sales comparison approach, and income capitalization method. The cost approach estimates property value by considering the cost of land acquisition, construction, and depreciation, making it useful for newly developed affordable housing units. The sales comparison approach evaluates property value based on recent transactions of similar properties, providing market-driven insights that are essential for investor confidence. The income capitalization method, which determines value by analyzing expected rental income and operating expenses, is particularly effective in assessing large-scale affordable housing portfolios. Emerging techniques, such as automated valuation models (AVMs) and artificial intelligence-driven predictive analytics, are enhancing accuracy and efficiency in portfolio valuation. AVMs use big data and machine learning algorithms to analyze market trends, property characteristics, and financial performance, reducing human bias and expediting decision-making. Additionally, discounted cash flow (DCF) analysis enables investors to project long-term returns and assess the financial viability of affordable housing investments. Integration of environmental, social, and governance (ESG) factors into valuation models is gaining traction, as sustainability considerations influence funding decisions. Access to capital remains a major challenge for affordable housing development. Accurate portfolio valuation enhances transparency, mitigates risk, and attracts funding from banks, private equity firms, and impact investors. Governments and housing agencies also use valuation data to design incentives, subsidies, and public-private partnerships to stimulate investment in low-income housing projects. This study concludes that adopting a combination of traditional and technology-driven valuation techniques strengthens real estate investment strategies and facilitates funding allocation for affordable housing. Future research should explore the impact of blockchain technology on real estate transactions and valuation accuracy.