In this paper, a novel bio-inspired optimization algorithm is proposed, called "Bombardier Beetle Optimizer (BBO)". This type of species is very intelligent, which has the ability to defense and escape from predators. The principles of the former one is inspired by the defense mechanism of the Bombardier Beetle against the predators, which the Bombardier Beetle triggers a toxic chemical spray when it feels threatened. This reaction occurs in a specialized reaction chamber inside its abdomen and includes a well-regulated enzymatic mechanism, which comprises hot water vapor, oxygen, and irritating substances like p-benzoquinones. In addition, the proposed BBO also simulates the escape mechanism of the Bombardier Beetle from a predator, which it has the ability to calculate its distance from the predator and it can fly away. The BBO is tested with optimizing six benchmark functions of "Congress on Evolutionary Computation (CEC 2017)" test bed suites. Moreover, it is compared against well-known metaheuristic optimization algorithms, including "Chernobyl Disaster Optimizer (CDO)", "Grey Wolf Optimizer (GWO)", "Particle Swarm Optimization (PSO)", "Bermuda Triangle Optimizer (BTO)", "Sperm Swarm Optimization (SSO)" and "Gravitational Search Algorithm (GSA)". The outcomes of this paper prove the BBO’s efficiency in which outperforms the other algorithms in terms of convergence rate and quality of results.