*Author Note: The preparation of this work was partly funded by a French National Research Agency ”Investissements d’avenir” program grant (ANR-15-IDEX-02) awarded to Hans IJzerman, and PRIMUS/20/HUM/009 grant awarded to Ivan Ropovik. Note that we wrote the pre-registration in past tense to avoid errors after finishing the manuscript.* **Summary** We conducted a **pre-registered** meta-analysis to provide our best estimate of the effect size of two stress regulation strategies: **Self-administered mindfulness meditation** and **Heart-Rate Variability biofeedback**. Our goal was to investigate whether the named strategies have any demonstrated efficacy in decreasing level of stress at the level of its components (physiological, affective, and cognitive) and in decreasing longer-term affective consequences of stress (i.e., depression, chronic anxiety; see [Study Rationale + Hypotheses][1] for details). To ensure an exhaustive coverage of the stress literature, we searched the literature using three databases: ProQuest (an online platform that integrates the results coming from three databases: APA PsycArticles, APA Psycinfo, ProQuest Dissertations & Theses Global‎), PubMED, and Scopus. For every database, we used a combination of keywords to find as many experimental and observational studies as possible, all of which highlighted a link between the two strategies and different components of stress (physiological, affective, and cognitive) and longer-term affective consequences of stress. All studies included human participants (see the [Methods][2] for precise information). To accommodate dependencies between effect sizes, we used a robust sandwich-type variance estimation (RVE; see Hedges, Tipton, & Johnson, 2010). We followed a stringent analysis workflow (using, in that order, a **permutation-based p-curve**, **4-parameter selection model** and **PET-PEESE**) to establish to what extent these stress regulation strategies are affected by publication bias and to establish their effect sizes (see the [Data Analytic Plan (Before Registration)][3] for precise information) We collected data starting May 30th and had created [the scripts beforehand][4]. We populated the [Data][5] and [Analytic Code (After Data Collection)][6] sections after our analyses were finished. In [Materials][7] you can find all the documentation that were used in the present meta-analysis. **Anticipated Timeline** Start data collection - 28th May 2020 Screening of studies - 10th June 2020 Data collection & coding- 31th August 2020 Data analysis - 30th September 2020 Writing conclusions and uploading data - 30th November 2020 [1]: https://osf.io/uwkxz/ [2]: https://osf.io/86r2s/ [3]: https://osf.io/58waj/ [4]: https://osf.io/58waj/ [5]: https://osf.io/vx3mk/ [6]: https://osf.io/ftqw7/ [7]: https://osf.io/dpj4r/