Blood pressure (BP) and heart rate (HR) are often captured in conjunction with weight in telemonitoring systems, but the additional prognostic potential of daily measurements of BP and HR in providing information on upcoming hospitalizations for worsening heart failure (HFH) have not been explored thoroughly. We retrospectively analyzed 267 daily home-telemonitored heart failure (HF) subjects. We extracted those episodes of HFHs that had sufficient data entries in the days leading up to hospitalization and tested the prognostic potential of 48 trend features based on weight, systolic BP, diastolic BP, pulse pressure (PP), and HR with a Naïve Bayesian model. The single best-performing trend feature - with a cross-validated estimate of 0.64 for the area under the curve (AUC) with a standard deviation (SD) of 0.01 - is based on a 2-day weight trend. The best multivariate feature set (cross-validated AUC = 0.70, SD= 0.01 comprises of 2-day trend features based on weight, systolic BP, and HR. There were large variations in the weight trends preceding hospitalizations and weight change alone had a modest predictive ability. Readily interpretable features capturing trends in BP and HR provided additional prognostic information and can be used for improving classification.