The relationship between solar irradiance and climate is greatly debated. This inferred relationship is often characterized via the statistical analysis of paleoclimate data. REDFIT is a commonly used statistical tool that overcomes uneven sampling to identify significant periodicities of variability in proxy data. We critically examine the use of REDFIT to identify solar signals in these data. By conducting a literature review, we show the REDFIT significance thresholds used by researchers to analyze paleoclimate data vary considerably. As there is some subjectivity and practicality involved in any statistical analysis, some variability is to be expected. However, we observe that the bulk of the significance thresholds used in the literature are less stringent than the critical false‐alarm level outlined by REDFIT's creators. We reexamine periodicities deemed “significant” in a published data set to show that using this more stringent, more objective critical false‐alarm threshold likely eliminates the previously inferred significance of solar signals in proxy data. Likewise, we address a lack of consideration of age model uncertainty on REDFIT's reliability in identifying solar periodicities. Overall, we show that the relationship between solar irradiance and climate, as identified by REDFIT analyses, may not be as robust as previous work might suggest.