This paper introduces the Chaotic Zebra Optimization Algorithm (CZOA), an enhanced version of the Zebra Optimization Algorithm (ZOA) designed to address the challenges for finding optimal solutions in complex optimization problems where traditional gradient-based methods are ineffective. The modification of this algorithm is initialization with a tent map on the population size while incorporating the ten other chaotic maps for better convergence rate. The range of the initial value for the chaotic maps [0, 1] is selected. The proposed Chaotic Zebra Optimization Algorithm (CZOA) with tent map applies on 23 standard benchmark functions for their complexity and diversity and obtain better solutions/results for fast convergence rate by using chaotic maps as well as comparison with another well-known established six metaheuristic algorithms. The obtained results are meticulously analyzed and depict the superiority of the CZOA and convergence rate. The CZOA with a tent map is more effective for solving real-world problems.