  Stars in the Asymptotic Giant Branch (AGB) phase, dominated by low to
intermediate-mass stars in the late stage of evolution, undergo periodic
pulsations, with periods of several hundred days, earning them the name Long
Period Variables (LPVs). These stars gradually shed their mass through stellar
winds and mass ejections, enveloping themselves in dust. Infrared (IR) surveys
can probe these dust-enshrouded phases and uncover populations of LPV stars in
the Milky Way. In this paper, we present a catalog of 159,696 Long Period
Variables using near-IR lightcurves from the Palomar Gattini - IR (PGIR)
survey. PGIR has been surveying the entire accessible northern sky ($\delta >
-28^{\circ}$) in the J-band at a cadence of 2-3 days since September 2018, and
has produced J-band lightcurves for more than 60 million sources. We used a
gradient-boosted decision tree classifier trained on a comprehensive feature
set extracted from PGIR lightcurves to search for LPVs in this dataset. We
developed a parallelized and optimized code to extract features at a rate of
~0.1 seconds per lightcurve. Our model can successfully distinguish LPVs from
other stars with a true positive rate and weighted g-mean of 0.95. 73,346
(~46%) of the sources in our catalog are new, previously unknown LPVs.
