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The ages of solar-like stars have been at the center of many studies such asexoplanet characterization or Galactic-archaeology. While ages are usuallycomputed from stellar evolution models, relations linking ages to other stellarproperties, such as rotation and magnetic activity, have been investigated.With the large catalog of 55,232 rotation periods, $P_{\rm rot}$, andphotometric magnetic activity index, $S_{\rm ph}$ from Kepler data, we have theopportunity to look for such magneto-gyro-chronology relations. Stellar agesare obtained with two stellar evolution codes that include treatment of angularmomentum evolution, hence using $P_{\rm rot}$ as input in addition to classicalatmospheric parameters. We explore two different ways of predicting stellarages on three subsamples with spectroscopic observations: solar analogs, late-Fand G dwarfs, and K dwarfs. We first perform a Bayesian analysis to deriverelations between $S_{\rm ph}$ and ages between 1 and 5 Gyr, and other stellarproperties. For late-F and G dwarfs, and K dwarfs, the multivariate regressionfavors the model with $P_{\rm rot}$ and $S_{\rm ph}$ with median differences of0.1%.and 0.2% respectively. We also apply Machine Learning techniques with aRandom Forest algorithm to predict ages up to 14 Gyr with the same set of inputparameters. For late-F, G and K dwarfs together, predicted ages are on averagewithin 5.3% of the model ages and improve to 3.1% when including $P_{\rm rot}$.These are very promising results for a quick age estimation for solar-likestars with photometric observations, especially with current and future spacemissions.

Magnetic activity evolution of solar-like stars: I. S_ph-Age relation derived from Kepler observations