This study presents a simplified method and empirical relationships for determining organic matter thermal maturity using a portable Raman system equipped with a 785 nm laser, for analysis of crushed, whole-rock samples. Several sets of rocks comprised of shale and coal samples with various mineralogical composition, thermal maturity, total organic carbon (TOC), and age were used to test the method and build correlations between Raman band separation (RBS) values and traditional thermal maturity indicators; organic matter reflectance (Ro) and programmed temperature pyrolysis (Tmax) values. Several sample preparation methods were tested on cuttings material and standard deviation values for RBS were minimized by washing, drying, and hand crushing the material to pass through a 40-mesh sieve, although less preparation can still yield reliable results. For the coal data set, Ro values range from 1.21-4.08% and correlated RBS values plateau at ~250 cm-1 above Ro=3.0% suggesting its correlative application below this maturity level. The second data set, comprised of disparate shale samples where both vitrinite and solid bitumen reflectance values were reported, have Ro values that range from 0.40-4.62%. Above 3.35% Ro, the corresponding RBS values plateau at ~290 cm-1, thus correlations were evaluated with a linear equation (R2= 0.96) between 0.40-3.35% Ro. Shale samples with Ro <2% and Tmax <551 were also used to correlate Tmax and RBS, yielding a linear correlation with an R2 of 0.94. The high degrees of correlation between whole rock RBS data and two thermal maturity indicators demonstrate the utility of this approach for generating source rock thermal maturity data from minimally processed whole rock samples which could easily be applied in field or laboratory settings. These datasets also highlight the utility of whole-rock thermal maturity techniques like programmed temperature pyrolysis and portable Raman spectroscopy versus microscopic maceral specific methods where analyst error (e.g., incorrect maceral identification) can yield potentially erroneous maturity correlations.