The relationship between corporate board attributes and dividend payout is already established yet mediating role of leverage in not been examined in Malaysian market. Therefore, this study aims to examine the mediating effect of financial leverage on the relationship between corporate board attributes and the dividend pay-out policy. A sample of 203 non-financial firms listed on the BURSA Malaysia between 2005 and 2018 were analysed using SmartPLS 3.0. The findings show that there is a partial mediating effect of financial leverage on the relationship between board members age, board diversity and dividend pay-out policy. Financial leverage also mediates the relationship between number of women on board, CEO-duality and dividend pay-out policy. However, financial leverage doesn’t mediate the relationship between board size and dividend pay-out policy. This study offers insights to policy-makers to develop a better corporate governance as well as a guidance to firms in the construction and implementation of their corporate governance policies in relation to financial leverage. This study also shed light on the influence of efficient corporate board attributes on dividend pay-out policy and financial leverage for firm growth. This study concludes that corporate board attributes impact capital structure and thus, firms may change its payout policy.

Abstract
 1. Introduction
 2. Literature Review
    2.1. Relationship between Corporate Board Attributes and Dividend Pay-out
    2.2. Relationship between Corporate Board Attributes and Financial Leverage
 3. Hypotheses Development
    3.1. Board Attributes Relationship with Financial Leverage
    3.2. The Effects of Corporate Board Attributes on Firm Dividend Pay-out Policy
    3.3. The Impact of Financial Leverage on Firm dividend Pay-out Policy
    3.4. The Mediating Role of Financial Leverage on the Relationship between Board Attributes and Firm’s Dividend Pay-out Policy
 4. Research Methodology
    4.1. Sample of the Study
    4.2. Dependent Variable
    4.3. Independent Variables
    4.4. Descriptive Statistics
 5. Empirical Results
    5.1. Model Fit
    5.2. Path Analysis
 6. Discussion and Conclusion
    6.1. Discussion
    6.2. Conclusion
 References

• Hussain TAHIR(IUMW Business School, Faculty of Business and Law, International University of Malaya-Wales)
• Ridzuan MASRI(IUMW Business School, Faculty of Business and Law, International University of Malaya-Wales)
• Mahfuzur RAHMAN(Faculty of Business and Accountancy, University of Malaya (UM)) Corresponding Author