Blood pressure is one vital sign that can predict and detect hypertensive on individuals. One prevalent problem in developing Asian countries is hypertension; and it has been a global health problem. The main objective of this study is to determine the BP of the patient by using Arduino-Based Sensors: SEN0213 Heart Rate Sensor and SEN0203 PPG Pulse Sensor using Pulse Transit Time (PTT). Linear and 4th Order Polynomial Regression is used to learn the equations to calculate the Systolic Blood Pressure (SBP) and Diastolic Blood Pressure (DBP) of the patients based on the Pulse Transit Time top and bottom (PTTt and PTTb) with DBP and SBP measured by a medical expert using clinical equipment. The researchers examined 30 individuals in order to incorporate equations in relation to SBP and DBP using PTT. P-values of the coefficients were less than 0.05, which means that the data entered for regression analysis were not by chance and that the coefficients were significant. A 84.06-84.61% and 67-71% of SBP and DBP data, respectively fit the model in an observation of 30. A 0.9199 and 0.8458 multiple R value for SBP and DBP is near 1, which means that both datasets have a nearly-perfect positive-relationship.