The expansion of multinational corporations into global markets presents both strategic opportunities and significant ethical challenges. Variations in regulatory frameworks, cultural norms, enforcement capacities, and stakeholder expectations create complex environments in which businesses must navigate issues of labor rights, corruption, corporate governance, and environmental sustainability. This study employs a computational and data-driven multidimensional approach to evaluate ethical performance across ten major industries and ten countries, leveraging advanced composite index modeling that incorporates interaction effects, penalty structures, and statistically normalized transparency scaling. By developing computationally refined models for Ethical Compliance, Corruption Risk, Labor Rights, and Environmental Sustainability, the research identifies sector-specific and region-specific vulnerabilities. High-risk sectors such as manufacturing, energy, and logistics demonstrate recurring deficiencies in labor practices and sustainability efforts, while industries such as pharmaceuticals and finance exhibit stronger governance and ethical alignment. Countries with weaker legal institutions and lower corruption perception scores exhibit elevated exposure to bribery and compliance failures. The findings highlight the need for data-driven ethical governance strategies that extend beyond compliance, embedding computational risk management into operational and strategic planning. This approach enables firms to better respond to stakeholder expectations, reduce reputational risks, and contribute to sustainable global development. The study offers practical implications for corporate leaders, policymakers, and scholars aiming to strengthen ethical standards in international business through computational and analytical frameworks.