Use　of　cellular　phone　while　driving　is　one　of　the　top　contributing　factors　that　induce　traffic　crashes,　resulting　in　significant　loss　of　life　and　property.　A　dilemma　zone　is　a　circumstance　near　signalized　intersections　where　drivers　hesitate　when　making　decisions　related　to　their　driving　behaviors.　Therefore,　the　dilemma　zone　has　been　identified　as　an　area　with　high　crash　potential.　This　article　utilizes　a　logit-based　Bayesian　network　(BN)　hybrid　approach　to　investigate　drivers＇　decision　patterns　in　a　dilemma　zone　with　phone　use,　based　on　experimental　data　from　driving　simulations　from　the　National　Advanced　Driving　Simulator　(NADS).　Using　a　logit　regression　model,　five　variables　were　found　to　be　significant　in　predicting　drivers＇　decisions　in　a　dilemma　zone　with　distractive　phone　tasks:　older　drivers　(50-60years　old),　yellow　signal　length,　time　to　stop　line,　handheld　phone　tasks,　and　driver　gender.　The　identified　significant　variables　were　then　used　to　train　a　BN　model　to　predict　drivers＇　decisions　at　a　dilemma　zone　and　examine　probabilistic　impacts　of　these　variables　on　drivers＇　decisions.　The　analysis　results　indicate　that　the　trained　BN　model　was　effective　in　driver　decision　prediction　and　variable　influence　extraction.　It　was　found　that　older　drivers,　a　short　yellow　signal,　a　short　time　to　stop　line,　nonhandheld　phone　tasks,　and　female　drivers　are　factors　that　tend　to　result　in　drivers　proceeding　through　intersections　in　a　dilemma　zone　with　phone　use　distraction.　These　research　findings　provide　insight　in　understanding　driver　behavior　patterns　in　a　dilemma　zone　with　distractive　phone　tasks.