Estimation of variance components is a statistical method used to decompose observed variability into components attributable to different sources of random variation, such as individual differences, measurement error, or environmental factors. This technique is crucial for mixed-effects models, enabling researchers to make inferences about population parameters and improve the precision of predictions in various fields like genetics, psychology, and engineering.