PromptWizard is an automated framework for optimizing prompts for large language models (LLMs). This system uses a self-evolving mechanism that iteratively refines prompts and examples through a feedback loop of generation, critique, and synthesis. PromptWizard aims to overcome the limitations of manual prompt engineering by improving task performance across diverse applications while also demonstrating cost-effectiveness compared to existing optimization strategies. The research demonstrates PromptWizard's effectiveness even with limited data and smaller LLMs, highlighting its practical utility.