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Plant biology is experiencing a renewed interest in the mechanistic underpinnings and evolution of phenotypic plasticity that calls for a re-evaluation of how we analyse phenotypic responses to a rapidly changing climate. We suggest that dissecting plant plasticity in response to increasing temperature needs an approach that can represent plasticity over multiple environments, and considers both population-level responses and the variation between genotypes in their response. Here, we outline how a random regression mixed model framework can be applied to plastic traits that show linear or nonlinear responses to temperature. Random regressions provide a powerful and efficient means of characterising plasticity and its variation. Although they have been used widely in other fields, they have only recently been implemented in plant evolutionary ecology. We outline their structure and provide an example tutorial of their implementation.