The COVID-19 pandemic exposed financial vulnerabilities as it subjected households to health shocks and income losses. With inequalities likely to deepen, policymakers may benefit from asking: What would make Filipinos financially resilient? This paper examines financial resilience in the Philippines by demographic profile and employs Logistic LASSO Regression, Decision Tree, and other machine learning models to create predictive models and generate inferences on determinants of financial resilience using data from the World Bank Global Financial Inclusion (Findex) surveys for 2017 and 2021. Variables were chosen based on the components of Salignac et al. (2019)’s Multidimensional Financial Resilience Framework. Empirical findings were consistent across models and suggest that demographics may provide higher predictive value for financial resilience than financial access. Income quintile, saving behavior, and gender emerged as the top predictors in both the 2017 and 2021 survey rounds. Age, saving for retirement, and online payments were also identified as important features for 2017, and tertiary education and medical borrowing for 2021. Insights from this study could provide policymakers with baseline information on financial resilience in the Philippines and support interventions to identify and empower the financially vulnerable towards financial security.