Natural experiments offer valuable opportunities for causal inference in psychology, despite being underutilized. Randomized experiments are preferred for their ability to eliminate alternative explanations, but they are often unethical or impractical. Observational studies, while feasible, lack the random assignment that makes randomized experiments causal. Natural experiments, which occur naturally and may create random or as-if random assignment, can bridge this gap. However, psychologists have rarely used them. Natural experiments include standard natural experiments, instrumental-variable designs, and regression-discontinuity designs. These methods allow researchers to study causal effects in real-world settings. For example, Lindqvist et al. (2020) used a lottery to study the effect of wealth on well-being, while Green & Winik (2010) used judicial calendars to examine the effect of incarceration on recidivism. Thistlethwaite & Campbell (1960) used test scores to assess the impact of academic recognition on performance. Natural experiments are challenging to find and may only provide information about specific causal effects. They also involve assumptions that are difficult to validate. However, they offer generalizability to real-world populations and contexts, making them valuable complements to randomized experiments. They can help assess whether effects observed in lab settings are relevant in the field. Psychologists should use natural experiments more often because they can be used when randomized experiments are unethical or unfeasible. They also reduce demand effects and provide more realistic conditions. Natural experiments can also help evaluate the relevance of causal effects in real-world settings. Despite their advantages, natural experiments are not a panacea. They rely on assumptions that are often hard to validate. Identifying and analyzing them requires specialized knowledge. Finding suitable natural experiments can also be challenging. Nevertheless, they offer attractive opportunities for causal inference, especially when randomized experiments are not feasible. This article highlights the importance of natural experiments in psychology and provides examples of their use. It encourages psychologists to explore these methods to enhance causal inference in their research.Natural experiments offer valuable opportunities for causal inference in psychology, despite being underutilized. Randomized experiments are preferred for their ability to eliminate alternative explanations, but they are often unethical or impractical. Observational studies, while feasible, lack the random assignment that makes randomized experiments causal. Natural experiments, which occur naturally and may create random or as-if random assignment, can bridge this gap. However, psychologists have rarely used them. Natural experiments include standard natural experiments, instrumental-variable designs, and regression-discontinuity designs. These methods allow researchers to study causal effects in real-world settings. For example, Lindqvist et al. (2020) used a lottery to study the effect of wealth on well-being, while Green & Winik (2010) used judicial calendars to examine the effect of incarceration on recidivism. Thistlethwaite & Campbell (1960) used test scores to assess the impact of academic recognition on performance. Natural experiments are challenging to find and may only provide information about specific causal effects. They also involve assumptions that are difficult to validate. However, they offer generalizability to real-world populations and contexts, making them valuable complements to randomized experiments. They can help assess whether effects observed in lab settings are relevant in the field. Psychologists should use natural experiments more often because they can be used when randomized experiments are unethical or unfeasible. They also reduce demand effects and provide more realistic conditions. Natural experiments can also help evaluate the relevance of causal effects in real-world settings. Despite their advantages, natural experiments are not a panacea. They rely on assumptions that are often hard to validate. Identifying and analyzing them requires specialized knowledge. Finding suitable natural experiments can also be challenging. Nevertheless, they offer attractive opportunities for causal inference, especially when randomized experiments are not feasible. This article highlights the importance of natural experiments in psychology and provides examples of their use. It encourages psychologists to explore these methods to enhance causal inference in their research.