Three procedures for classifying an entity into one of the two predetermined univariate populations 1__ampersandsignnbsp;and ?2 were derived, evaluated and compared. This paper proposes Unspecified structure of the__ampersandsignnbsp;variance, Regression Discriminant (RD) and Elongated Discriminant (ED) procedures for the classification using k repeated observations collected on each entity j at time t (t = 1,2,__ampersandsignhellip;, k;j = 1,2,__ampersandsignhellip;,ni; i = 1,2). Mean arterial pressure which is a function of systolic and diastolic blood pressures were collected sequentially in time from two sampled populations ?1(survivors) and ?2 (nonsurvivors), of hypertensive patients admitted at the Jos University Teaching Hospital (J.U.T.H).Three techniques: re-substitution, leave __ampersandsignndash; one out and partitioning of samples are used to construct and evaluate the sample based classification rules. Probabilities of misclassification obtained from the confusion matrices produced by these techniques are used to compare the performances of these rules. The analysis reveals that the procedures compare favourably with one another and the Fisher__ampersandsignrsquo;s commonly used rule. The classification rule obtained using Elongated Discriminant procedure performs better with lower error rates. This is followed by unspecified structure of the variance and regression discriminant procedure in that order.