This study examines portfolio optimization in the Philippine Stock Exchange (PSE) Industrial Sector by integrating Mean-Variance Theory (MVT) with the Security-Potential/Aspiration (SP/A) framework. Using data from 73 industrial firms from 1993 to 2022, expected returns were estimated through a rolling-window approach. Portfolio optimization was performed under varying Risk-Return Factor (RRF) levels, reflecting bearish and bullish investment preferences, while investor decision-making was modeled under a cautiously hopeful condition in which fear and hope were equally weighted. Behavioral probability assignments were generated using different SP/A parameter levels and incorporated into the optimization process. The resulting portfolios were evaluated against a benchmark portfolio and the PSE. Results show that portfolios incorporating behavioral probability assignments achieved superior risk-adjusted performance, with balanced risk-return preferences producing the most favorable outcomes, while highly return-focused portfolios exhibited greater volatility. These findings demonstrate the value of incorporating behavioral factors into portfolio optimization and investment decision-making in emerging markets.